Copyright TechTarget - All rights reserved ComputerWeekly’s best articles of the day https://cyber.law.harvard.edu/rss/rss.html Techtarget Feed Generator en Sun, 10 May 2026 07:06:19 GMT https://www.computerweekly.com editor@computerweekly.com <p>The prevailing anxiety in boardrooms is that artificial intelligence (AI), fuelled by recent breakthrough <a href="https://www.computerweekly.com/opinion/Anthropics-Mythos-raises-the-stakes-for-security-validation">advancements in frontier models</a>, will soon unleash a wave of autonomous cyber attacks against corporate defences.</p> <p>Tony Anscombe, chief security evangelist at cyber security firm ESET, would like everyone to take a collective breath. “Some people I talk to think, ‘AI is attacking us’,” Anscombe said in a recent interview with Computer Weekly. “No, AI is not attacking you. We’re not quite a Terminator yet.”</p> <p>Instead of deploying omnipotent digital adversaries, modern cyber criminals are acting like efficiency experts, integrating AI tools to automate mundane but highly effective tasks: <a href="https://www.computerweekly.com/feature/Beyond-the-hook-How-phishing-is-evolving-in-the-world-of-AI">drafting flawless phishing emails</a>, mimicking executives in messages and automating the hunt for stolen credentials.</p> <p>The reason hackers haven’t unleashed fully autonomous AI models to attack networks, Anscombe argued, boils down to simple economics: they don’t need to.&nbsp;</p> <p>“There’s a lot of low-hanging fruit already,” he said, noting that basic internet scans continually reveal poorly secured remote-access systems and virtual private networks. “There are still a lot of organisations out there that publicly expose weaknesses. That means the cyber criminal has too much opportunity already.”</p> <p>But the seeds of next-generation, AI-driven malware are already being sown, sometimes by accident. Anscombe pointed to a recent incident involving researchers at a New York university who successfully developed a proof-of-concept malware that uses an AI prompt mechanism. Once inside a system, the malware could dynamically analyse the digital environment, rewrite its own script on the fly, and independently decide whether to steal data. The researchers, however, inadvertently published the source code to a public malware-testing database.</p> <p>“Once you put something out in the public domain, then somebody else can take it, reverse engineer it, modify it and reuse it for their own purposes,” Anscombe said. “Suddenly, you’ve got the work already done for cyber criminals.”</p> <p>While mainstream hackers are not yet using such tools, ESET researchers have begun tracing similar sophisticated tactics back to state-aligned hacking groups.</p> <section class="section main-article-chapter" data-menu-title="The view from the inside"> <h2 class="section-title"><i class="icon" data-icon="1"></i>The view from the inside</h2> <p>For chief information security officers (CISOs), external hackers are only half the battle. Faced with intense pressure from chief executives and corporate boards, many senior leaders are doubling down on AI to stay ahead of competitors.</p> <p>The immediate risk, Anscombe noted, comes from well-meaning employees pasting sensitive corporate data or customer information into <a href="https://www.computerweekly.com/news/366555516/How-APAC-organisations-are-tapping-generative-AI">generative AI (GenAI) tools</a>, potentially running afoul of privacy laws.</p> <p>As such, Anscombe called for CISOs to establish clear governance policies on the use of tools such as OpenAI’s ChatGPT or Microsoft Copilot to prevent staff from sharing sensitive personal or corporate data with public models.</p> <p>When it comes to AI agents, Anscombe noted that because agents act independently, they could expand a company’s attack surface and inadvertently grant access to sensitive data or facilitate lateral movement by bad actors.</p> <p>To mitigate these risks, security teams must treat AI software less as traditional code and more as digital workers. “You need to make sure the agents have permissions in the same way that employees have limitations on their access rights,” Anscombe said. “You need to treat them, in some ways, like humans.”</p> <p>As AI risks multiply, the CISO’s job description is evolving too. “I think the CISO is fast becoming a business operations person, and they&nbsp;need to start understanding the business flow and the operational flow of the business to be able to help protect it,” Anscombe observed.</p> <p>On the operational level, <a href="https://www.computerweekly.com/opinion/How-AI-agents-are-driving-the-future-of-security-operations">security operations centres (SOCs) are starting to rely heavily on machine learning and AI</a> to filter massive amounts of telemetry and prevent human analysts from being overwhelmed. AI systems act like investigators, gathering evidence, highlighting anomalies and assigning probability scores, so the human analyst can make the final determination on sophisticated threats.</p> <p>However, organisations, particularly small and medium-sized enterprises (SMEs) that lack a dedicated team of specialised security analysts, can consider outsourcing to <a href="https://www.computerweekly.com/microscope/feature/How-to-sell-MDR">managed detection and response</a> (MDR) providers rather than treating security tooling as a compliance checklist, Anscombe said.</p> <p>“You can’t deploy something like <a href="https://www.computerweekly.com/news/252468781/How-EDR-is-moving-beyond-the-endpoint">EDR [endpoint detection and response]</a> and then forget it. It’s not a tick box. It needs to be managed and operated, otherwise it’s ineffective,” he added.</p> <p>Ultimately, Anscombe hopes to separate the existential dread surrounding AI from reality. He pointed to the Indian government’s use of facial recognition at a New Delhi train station, a project that successfully identified and reunited thousands of missing children with their parents in a matter of weeks. “We shouldn’t fear technology. We should make sure we use it responsibly,” he said.</p> <p>Part of that responsibility, he said, is dialling back the marketing hype that fuels public anxiety. “I saw recently an oven that claims to cook your dinner using AI,” he said, explaining that the appliance merely uses a basic moisture sensor to know when a cake is baked. “That’s a lookup table, not AI. The overuse of the word ‘AI’ doesn’t help the fear issue.”</p> <div class="pro-features-wrapper"></div> <div class="extra-info"> <div class="extra-info-inner"> <h3 class="splash-heading">Read more about cyber security in APAC</h3> <ul class="default-list"> <li>Singapore mobilised over 100 cyber defenders to neutralise a sophisticated APT actor which infiltrated Singtel, StarHub, M1 and Simba networks in the country’s <a href="https://www.computerweekly.com/news/366638973/Singapore-mounts-largest-ever-cyber-operation-to-oust-APT-actor">largest coordinated cyber incident response to date</a>.</li> <li>Japan’s Nikkei has confirmed a major data breach that potentially <a href="https://www.computerweekly.com/news/366634243/Nikkei-data-breach-exposes-personal-data-of-over-17000-staff">exposed the personal information of more than 17,000 employees</a> and business partners after hackers infiltrated its internal Slack messaging platform.</li> <li>Australian privacy commissioner warns that the <a href="https://www.computerweekly.com/news/366633983/Fewer-data-breaches-in-Australia-but-human-error-now-a-bigger-threat">human factor is a growing threat</a> as notifications caused by staff mistakes rose significantly even as total breaches declined 10% from a record high.</li> <li>Philippine bank <a href="https://www.computerweekly.com/news/366633428/BDO-Unibank-taps-Zscaler-to-secure-cloud-migration">BDO is shoring up its cyber security capabilities</a> to protect its data and systems as it moves more services to the cloud and expands its physical presence into remote areas of the archipelago.</li> </ul> </div> </div> </section> While fully autonomous hacking bots remain a distant reality, an ESET expert warns that AI is quietly supercharging phishing schemes and creating new vulnerabilities inside organisations https://cdn.ttgtmedia.com/visuals/German/article/artificial-intelligence-robot-adobe.jpg https://www.computerweekly.com/news/366642914/ESET-Dont-fear-the-AI-Terminator-but-prepare-for-agent-risks Fri, 08 May 2026 06:30:00 GMT <p>Organisations racing to implement <a href="https://www.gartner.com/en/insights/generative-ai-for-business">generative AI</a> (GenAI) find themselves caught between the pressure to innovate and the reality of what it takes to actually do so. As a result, Gartner research found at least 50% of GenAI projects were abandoned after proof of concept by the end of 2025.</p> <p>When applied well, GenAI can help organisations tackle complex challenges and build sustainable competitive advantage. When applied poorly, it becomes just another costly experiment.</p> <p>The single biggest reason GenAI fails isn’t with the technology itself - it’s how organisations approach implementation. Organisations that don’t establish specific success metrics and align GenAI with strategic objectives face the highest failure rates. GenAI must be treated as a business transformation initiative, not just a technology deployment.</p> <p>To realise meaningful results from GenAI investments, leaders must look beyond hype and address the core reasons many projects fail. Understanding these pitfalls and knowing how to avoid them can be the difference between wasted resources and lasting competitive advantage.</p> <section class="section main-article-chapter" data-menu-title="Lack of business value"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Lack of business value</h2> <p>The most fundamental reason GenAI projects fail is lack of business value. Many organisations fall into the trap of chasing flashy demos or deploying GenAI everywhere simultaneously. This approach dilutes resources across low-impact initiatives.</p> <p>Without clear prioritisation frameworks or defined success metrics, projects lack measurable business value, making them vulnerable when budgets tighten or executives demand proof of ROI.&nbsp;</p> <p>To succeed, organisations should create a rigorous AI use-case prioritisation framework that aligns with overall AI ambition and technical feasibility. It is essential to identify specific measurable outcomes, such as productivity gains, cost reductions and customer satisfaction, and track progress continuously.</p> </section> <section class="section main-article-chapter" data-menu-title="Data isn’t ready"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Data isn’t ready</h2> <p><a href="https://www.gartner.com/en/newsroom/press-releases/2026-04-16-gartner-says-organizations-with-successful-ai-initiatives-invest-up-to-four-times-more-in-data-and-analytics-foundations">Data quality</a> is the foundation of any successful GenAI initiative. Poor data affects every department, leading to unreliable outputs, failed <a href="https://www.computerweekly.com/feature/Understanding-RAG-architecture-and-its-fundamentals">retrieval augmented generation</a> (RAG) implementations and models that can't be fine-tuned effectively.</p> <div class="pro-features-wrapper"></div> <p>Building an&nbsp;AI-ready data&nbsp;foundation is critical for scaling GenAI efforts. This means curating accurate, enriched and well-governed data across the enterprise, while investing in training teams on specialised data management for GenAI use cases.</p> <p>Specifically, organisations should focus on creating robust pipelines for RAG, organising and retrieving information with knowledge graphs. These all contribute to more reliable outcomes.</p> </section> <section class="section main-article-chapter" data-menu-title="Escalating total cost of ownership"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Escalating total cost of ownership</h2> <p>Rising costs kill projects even when they’re technically successful and delivering user value. What appears as negligible per-token expenses during pilots can become a total cost of ownership nightmare when multiplied across thousands of users and hundreds of use cases.</p> <p>Organisations often underestimate GenAI’s operational expenses due to limited visibility into how costs scale. Projects that appear viable in proof of concept become budget black holes in production, leading to abrupt cancellation.&nbsp;</p> <p>To avoid this outcome, <a href="https://www.computerweekly.com/news/366641816/How-the-AI-boom-is-reshaping-tech-cost-management">GenAI FinOps&nbsp;practices</a> should be adopted from day one. Educate all stakeholders – not just IT – on cost implications tied to deployment approaches, model selection and token usage, and avoid unnecessary model customisation, which can be expensive.</p> <p>It is also important to apply prompt caching strategies to reduce redundant <a href="https://www.computerweekly.com/feature/Enterprise-strategies-for-API-management">application programming interface</a> (API) calls; use model routing to route queries to appropriately sized models; and monitor costs continuously with proper allocation and visibility tools.</p> </section> <section class="section main-article-chapter" data-menu-title="Responsible AI as an afterthought"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Responsible AI as an afterthought</h2> <p>Neglecting <a href="https://www.computerweekly.com/feature/Why-responsible-AI-is-a-business-imperative">responsible AI</a> exposes organisations to regulatory violations, reputational damage, user harm and project shutdowns – risks that resonate with the C-suite and the board.</p> <p>GenAI perpetuates existing AI risks while introducing new ones like deepfakes and hallucinations. Without robust controls around safety, privacy, accountability and fairness, these risks multiply quickly.</p> <p>Responsible AI must be central from the beginning. day one. This means focusing on safety through the prevention of harmful outputs and ensuring model reliability, as well as privacy by protecting sensitive information. Accountability by establishing clear governance and ownership is also important, as well as fairness to avoid bias while ensuring equitable outcomes for all stakeholders involved.</p> <p>Equally important is implementing critical tools, like <a href="https://www.computerweekly.com/feature/Assessing-the-risk-of-AI-in-enterprise-IT">model input validation and filtering</a>; output monitoring and observability systems; compliance tracking and audit trails; and security controls for data and model access. Defining where GenAI shouldn’t be used is also an important consideration to protect against predictable disasters.</p> </section> <section class="section main-article-chapter" data-menu-title="Poor change management"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Poor change management</h2> <p>Without change management, even technically excellent GenAI tools see minimal adoption. Usage drops over time. Employees feel threatened rather than empowered. The organisation captures a fraction of potential value, while technical teams wonder why their capable solution sits unused.&nbsp;</p> <p>Change management must be treated as a first-class requirement, not an afterthought. Leaders need to build empathy maps that reveal how GenAI impacts roles throughout their organisation, so they can focus on amplifying human capabilities instead of threatening job security.</p> <p>To make it easier for employees to adopt GenAI, build it into existing workflows if possible rather than requiring them to use new tools and processes. Also, involve them in the pilot to ensure the user experience is acceptable to them and make changes based on feedback. This will increase the chances of them actually using the technology in the long-term.</p> <p><i>Arun Chandrasekaran is a distinguished vice-president analyst at Gartner, specialising in AI. </i></p> </section> With half of all generative AI projects failing after the proof-of-concept stage, organisations are discovering that technology alone isn't a silver bullet. Here’s how to turn them into lasting competitive advantages https://cdn.ttgtmedia.com/visuals/ComputerWeekly/HeroImages/generative-AI-Chat-GPT-Timon-adobe.jpg https://www.computerweekly.com/opinion/Why-50-of-GenAI-projects-fail-and-how-to-beat-the-odds Fri, 08 May 2026 02:43:00 GMT <p>As ride-hailing bookings plummeted by nearly 80% at the peak of the <a href="https://www.computerweekly.com/essentialguide/Essential-Guide-Technology-readiness-for-the-Covid19-coronavirus-crisis">Covid-19 pandemic</a>, Ken Lek and his finance team at Grab were using a spreadsheet with 47 tabs to build scenario plans should lockdowns continue to persist.</p> <p>Meanwhile, food deliveries surged but Grab’s internal systems were too fragmented to keep pace. Its finance team pulled numbers from one source and operations from another, forcing teams to spend weeks manually verifying and reconciling data.</p> <p>“The infrastructure behind those numbers was not where it needed to be,” said Lek, managing director and head of strategic finance and investor relations at Grab, at the AWS Summit Singapore conference today. “We were making existential decisions for the company serving millions of people. That experience left a mark on me – not just the stress of it, but the conviction that it has fundamentally changed how Grab’s finance function operated.”</p> <p>The harrowing experience led to Project Grabhouse, an effort to rebuild Grab’s entire data foundation on AWS using storage such as <a href="https://www.techtarget.com/searchaws/definition/AWS-bucket">Amazon S3</a> and open table formats like <a href="https://www.techtarget.com/searchdatamanagement/opinion/Why-Apache-Iceberg-is-essential-for-modern-data-lakehouses">Apache Iceberg</a>. The result was a governed, centralised data lake that acts as a single source of truth for the entire company.</p> <p>The operational impact was notable. Manual data reconciliation dropped by up to 60%, while cost allocations could be traced to the individual support agent and ticket. This exactness in unit economics – vital in an industry where margins are measured in cents – helped Grab report its first full year of net profit in 2025, reaching $200m while handling hundreds of millions of monthly transactions.</p> <p>Now, Grab is layering Bricks, its enterprise AI platform, on top of the Grabhouse data lake. This unified foundation allows teams to build automation workflows and deploy artificial intelligence (AI) agents at scale without writing any code.</p> <p>“For the first time in my career, I can see a path where strategic finance teams spend most of our time on actual strategy and advising leadership, navigating complexity, rather than on extracting and reconciling data,” Lek said. “The first decade of Grab was about scale, the next decade is about intelligence.”</p> <section class="section main-article-chapter" data-menu-title="Orchestrating the frontlines"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Orchestrating the frontlines</h2> <p>At the event, Ng Tian Beng, president and group CEO at Certis, a security service provider, also showed how AI is being deployed in frontline and physical security operations.</p> <p>The former Dell executive shared the stage with two different faces of the new workforce: Max, a multi-service autonomous robotic concierge; and Ace, an autonomous robotic dog used for complex security patrols. Both robots are wired into Mozart, a centralised operational platform powered by AI that helps human operators detect anomalies, understand context and orchestrate real-time responses.</p> <p>“We don’t use AI just to generate insights. We use it to orchestrate decisions in our operations, to coordinate resources and to drive action in the real world,” Ng said. “The question is no longer if AI will transform operations – that’s a given. The real question is, ‘How quickly can we bring together these technologies out of the lab and into the real world so that we can really make a difference?’”</p> <p>If this integration is done well, the outcomes extend far beyond efficiency, Ng said. By offloading physically demanding and higher-risk tasks to robots, security officers are freed up to focus on work that requires complex judgement, empathy and human interaction.</p> <p>Crucially, Ng stressed that achieving these outcomes relies on a bedrock of strong cyber security and trust. It is not enough that the system works – the operators on the ground must be able to understand and trust the technology to respond reliably.</p> </section> <section class="section main-article-chapter" data-menu-title="Bridging the SME maturity gap"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Bridging the SME maturity gap</h2> <p>While larger firms such as Grab and Certis are maturing in their AI journey, many of Singapore’s small and medium-sized enterprises (SMEs) are struggling to move past the initial adoption phase.</p> <div class="pro-features-wrapper"></div> <p>Research by Strand Partners, commissioned by AWS and released at the summit, revealed that while 75% of financial services SMEs and 61% of healthcare SMEs in Singapore use AI, only a small fraction have progressed to advanced use where AI is integrated across core functions.</p> <p>“ <!--StartFragment--><span data-olk-copy-source="MessageBody">Singapore's SMEs have moved decisively on AI. The next step is making that investment sustainable by integrating AI across functions so it shifts from a point solution to a core part of how the businesses run</span>,” said Priscilla Chong, managing director of AWS Singapore.</p> <p>Chong noted that the most successful companies employ a dual strategy: a safe environment for open experimentation, paired with strict guardrails for real-world production.</p> </section> <section class="section main-article-chapter" data-menu-title="Upskilling workers and students"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Upskilling workers and students</h2> <p>In his keynote address, Desmond Tan, deputy secretary-general of the National Trades Union Congress (NTUC) and senior minister of state in the prime minister’s office, noted that “AI should not result in jobless growth and productivity gains should never come at the expense of our workers”.</p> <p>He pointed to NTUC’s Company Training Committees (CTCs), which have already uplifted more than 300,000 workers, and a partnership between NTUC and AWS that aims to support at least 100 companies in their business transformation and expand AI skills access for 10,000 workers.</p> <p>To secure the talent pipeline needed for an AI-driven economy, AWS also announced a major initiative for Singapore’s institutes of higher learning (IHLs).</p> <p>Eligible students and adult learners at polytechnics, Institute of Technical Education (ITE) colleges and universities will receive 1,000 complimentary <a href="https://www.techtarget.com/searchsoftwarequality/news/366627715/AWS-Kiro-coding-agents-highlight-spec-driven-development">Kiro</a> credits, a 20-fold increase from the standard free tier. Kiro is a professional-grade AI developer tool that focuses on <a href="https://www.techtarget.com/searchsoftwarequality/news/366627715/AWS-Kiro-coding-agents-highlight-spec-driven-development">specification-driven development</a>, requiring users to define a project’s scope, scenarios and success criteria before any code is generated.</p> <p>“Vibe coding is telling a contractor to just start building. Spec-driven development is the blueprint that comes first – and what gets built with the blueprint is something a team, an employer or an SME can actually depend on,” said Elsie Tan, country manager for worldwide public sector Singapore at AWS. “That is the standard we want Singapore’s IHL graduates to meet.”</p> <p>To close the gap between classroom theory and industry needs, AWS will also launch an AWSome Lab in July 2026. The web-based portal will allow Singapore businesses to submit real-world problem statements, which educators can assign to students. The students will then build and document proof-of-concept AI solutions, turning their coursework into career-ready experience.</p> <div class="extra-info"> <div class="extra-info-inner"> <h3 class="splash-heading">Read more about AI in APAC</h3> <ul class="default-list"> <li>Agoda, a digital travel platform, has set its sights on&nbsp;<a href="https://www.computerweekly.com/news/366640804/Agoda-scales-AI-strategy-opens-new-APAC-tech-hub">becoming an AI-powered travel companion</a>&nbsp;as it changes how it builds software and moves its tech workforce into a new facility in Bangkok.</li> <li>Singtel and Nvidia have teamed up on a multimillion-dollar facility to&nbsp;<a href="https://www.computerweekly.com/news/366639492/Singtel-Nvidia-to-help-scale-enterprise-AI-deployments">help organisations scale enterprise AI deployments</a>, tackle extreme datacentre power densities, and prepare for the era of embodied AI.</li> <li>The Australian government has struck a&nbsp;<a href="https://www.computerweekly.com/news/366639595/Australia-inks-five-year-deal-with-Microsoft-to-drive-AI-and-cloud-adoption">five-year volume sourcing agreement with Microsoft</a>&nbsp;to speed up adoption of AI and cloud technologies across the public sector.</li> <li>Alibaba Group has unveiled&nbsp;<a href="https://www.computerweekly.com/news/366640461/Alibaba-joins-AI-agent-race-with-Wukong-launch">Wukong</a>, an AI-native enterprise platform that brings advanced agentic AI capabilities directly into business workflows.</li> </ul> </div> </div> </section> At AWS Summit Singapore, Certis and Grab showed how they are embedding AI in their business, such as automating finance operations and deploying robots in public safety and security patrols https://cdn.ttgtmedia.com/visuals/German/Ai-KI-robot-with-machine-Summit-Art-Creations-Adobe.jpg https://www.computerweekly.com/news/366642816/How-Singapore-firms-are-scaling-AI-initiatives Wed, 06 May 2026 06:40:00 GMT <p>The days of the glorified artificial intelligence (AI) chatbot are over, with more enterprises <a href="https://www.computerweekly.com/feature/Moving-agentic-AI-from-innovation-theatre-to-enterprise-production">starting to embrace the era of autonomous agents</a> rummaging through corporate data.</p> <p>At the recent Google Cloud Next 2026 conference in Las Vegas, Google took the wraps off its Agentic Data Cloud, a rebranding and architectural effort to support the transition from passive systems of intelligence to autonomous systems of action.</p> <p>“Everyone’s talking about systems of intelligence, but frankly, they’re still ingesting all the data, looking at the past or maybe trying to predict the future,” said Andi Gutmans, general manager and vice-president for Data Cloud at Google.</p> <p>“We’re moving from human scale to agent scale, both in the number of agents we’re going to have and the workloads we have to manage,” he told Computer Weekly, referring to the exponential growth in compute requirements of agentic AI.</p> <p>To address the workload, cost and governance issues associated with agentic AI, Google unveiled around 80 new product updates, focusing on metadata management, cross-cloud interoperability and distributed database capabilities.</p> <p>A primary concern for enterprise data teams deploying AI agents is ensuring models access the right data while respecting access controls. Gutmans noted that simply knowing where data resides no longer suffices – agents need semantic context to avoid hallucinations and errors.</p> <p>“It’s typical for customers to have 500 customer tables, but which table do you want to look at?” Gutmans said. In response, Google launched the <a href="https://www.techtarget.com/searchdatamanagement/news/366641929/Google-unveils-data-cloud-purpose-built-for-agentic-AI">Knowledge Catalog</a>, which builds on its previous Dataplex governance capabilities and aggregates metadata from within Google Cloud, external cloud applications and third-party catalogues. It then enriches the metadata to map relationships across structured and unstructured data.</p> <p>Gutmans described Knowledge Catalog as a “flywheel” built directly on top of existing access controls, ensuring agents cannot surface or act on data they are not authorised to view.</p> <p>Recognising the realities of heterogeneous IT environments, Google also introduced the Cross-Cloud Lakehouse. The offering allows enterprises to run Google’s <a href="https://www.computerweekly.com/feature/Big-data-and-Google-BigQuery-improve-cancer-drug-development-by-detecting-bacteria">BigQuery</a> and AI capabilities against data residing in Amazon Web Services and Microsoft Azure, while also providing zero-copy integrations with enterprise systems like SAP and Workday.</p> <p>Gutmans was keen to split hairs on the terminology: “It’s very important to note that the term ‘cross-cloud’ is distinct from ‘multicloud’; those who refer to multicloud are just talking about multiple single-cloud environments.”</p> <p>Another significant update was Spanner Omni. Historically, Google Cloud Spanner, a globally distributed relational database, was tethered to Google’s infrastructure, including storage, as well as GPS receivers and atomic clocks to ensure transactional consistency.</p> <p>Driven by enterprise demand for disconnected edge and on-premises deployments via Google Distributed Cloud, Google has engineered Spanner to run independently.</p> <p>“Three to four years ago, no one, including us, believed we could disconnect Spanner from Google Cloud,” Gutmans said. Now, Spanner Omni offers vector processing, search and graph capabilities for disconnected environments, which Gutmans noted is key for highly regulated use cases like on-premise fraud detection.</p> <section class="section main-article-chapter" data-menu-title="The IT pro as orchestrator"> <h2 class="section-title"><i class="icon" data-icon="1"></i>The IT pro as orchestrator</h2> <p>As part of the Agentic Data Cloud roll-out, Google released a Data Agent Kit, featuring support for <a href="https://www.techtarget.com/searchenterpriseai/news/366624572/Anthropic-intros-next-generation-of-Claude-AI-models">Claude Code</a>, Gemini CLI, Codex, and VS Code extensions. The goal is to provide developers and data engineers with the model context protocol (MCP) and tools necessary to build their own agents.</p> <p>According to Gutmans, the move towards agentic AI means that rather than writing manual pipelines or Python scripts, practitioners will engage in “intent-driven development”, which allows them to focus on defining their goals and desired outcomes while the agents handle the technical implementation.</p> <p>“Every practitioner is now becoming an orchestrator of agents,” Gutmans said. “That will be true whether you’re a business user, data scientist, data analyst, data engineer or developer. We are really trying to...put this persona in a position where they have a team of agents, and they’re orchestrating the agents.”</p> <p>Serving in a dual role where he provides data infrastructure for Alphabet properties like Search, YouTube and Gmail, Gutmans noted that Google’s own <a href="https://www.techtarget.com/searchitoperations/definition/site-reliability-engineering-SRE">site reliability engineering</a> (SRE) teams are already deploying AI agents.</p> <p>“One example is an agent that looks at support tickets. If it sees that there’s more than one support ticket in a given period of time that looks very similar, it will page us and say, ‘Hey, maybe something bigger is happening here’,” Gutmans said.</p> <p>With the slew of enhancements in Agentic Data Cloud, Gutmans didn’t shy away from throwing a bit of shade at rivals, claiming Google’s ownership of the full stack – from custom tensor processors and BigQuery to DeepMind’s Gemini models – leaves rivals in the dust.</p> <p>“If you think about other hyperscalers like Azure, they don’t have the model, so they end up having to connect to some other environment,” he claimed. As for pure-play data platform suppliers like Databricks? “They neither have the infrastructure nor the model, so they’re basically kind of assembling all this stuff.”</p> <p>Moutusi Sau, managing vice-president at Gartner, said Google’s Agentic Data Cloud reframes the hyperscaler’s data platform as a semantic and orchestration layer for agents, addressing challenges such as agent failures, which are often caused by poor data context, inconsistent semantics, and fragile integration.</p> <p>Capabilities such as zero-copy and cross-cloud access reduce data gravity and duplication, but they also increase dependence on semantic accuracy, metadata governance and performance consistency, she added.</p> <p>Ultimately, Sau called for enterprises to invest as much in semantic ownership, stewardship and validation as they did in tooling. “Without disciplined governance, enterprises risk scaling ambiguity and mistrust faster than agents scale productivity,” she said.</p> <div class="pro-features-wrapper"></div> <div class="extra-info"> <div class="extra-info-inner"> <h3 class="splash-heading">Read more about AI in APAC</h3> <ul class="default-list"> <li>Agoda, a digital travel platform, has set its sights on <a href="https://www.computerweekly.com/news/366640804/Agoda-scales-AI-strategy-opens-new-APAC-tech-hub">becoming an AI-powered travel companion</a> as it changes how it builds software and moves its tech workforce into a new facility in Bangkok.</li> <li>Singtel and Nvidia have teamed up on a multimillion-dollar facility to <a href="https://www.computerweekly.com/news/366639492/Singtel-Nvidia-to-help-scale-enterprise-AI-deployments">help organisations scale enterprise AI deployments</a>, tackle extreme datacentre power densities, and prepare for the era of embodied AI.</li> <li>The Australian government has struck a <a href="https://www.computerweekly.com/news/366639595/Australia-inks-five-year-deal-with-Microsoft-to-drive-AI-and-cloud-adoption">five-year volume sourcing agreement with Microsoft</a> to speed up adoption of AI and cloud technologies across the public sector.</li> <li>Alibaba Group has unveiled <a href="https://www.computerweekly.com/news/366640461/Alibaba-joins-AI-agent-race-with-Wukong-launch">Wukong</a>, an AI-native enterprise platform that brings advanced agentic AI capabilities directly into business workflows.</li> </ul> </div> </div> </section> As enterprises move from reactive analytics to AI agents, Google Cloud’s data chief details new metadata, cross-cloud and database tools to help them govern and scale AI agents https://cdn.ttgtmedia.com/visuals/ComputerWeekly/HeroImages/abstract-tech-AI-data-spainter-vfx-adobe.jpg https://www.computerweekly.com/news/366642734/Googles-Agentic-Data-Cloud-to-power-systems-of-action Tue, 05 May 2026 03:36:00 GMT <p>Experience management software provider Qualtrics recently held its Experience Live event in Sydney, where several high-profile customers in Australia and New Zealand (ANZ) took to the stage to share their experiences using <a href="https://www.computerweekly.com/resources/Artificial-intelligence-automation-and-robotics">artificial intelligence (AI)</a> to harness enterprise data.</p> <p>Sonny Sethi, senior director of market research at flexible payments provider Zip Co, pointed out that the research process has changed significantly thanks to artificial intelligence (AI). Studies that previously took months are now being completed in days, and data from multiple sources – such as app store reviews and Net Promoter Scores (NPS) – can be combined much more easily.</p> <p>Sethi also noted the growing decentralisation of data insights. Where this was once a heavily centralised function, it is becoming part of the job description for a wide range of roles, requiring organisations to provide broader access to research data.</p> <p>Zip Co is enabling this through its Zip Insights <a href="https://www.computerweekly.com/feature/LLMs-explained-A-developers-guide-to-getting-started">large language model</a> (LLM), which is built on three years’ worth of research reports and used for brainstorming and other commercial functions.</p> <p>“You want to open your tools and research platforms to as many people as possible within Qualtrics,” Sethi advised. However, he warned against simply making raw research data available; staff must be trained to understand and correctly interpret the data, and to use appropriate prompts to get what they need from the LLM.</p> <p>Employees also need to be alerted to the existence of new data. Because Zip Co is a heavy user of Slack, Sethi has deployed a Qualtrics Slack connector to disseminate research findings in real time. The goal is for insights to appear natively in all the tools and platforms employees use on a daily basis, whether that is Figma, Jira or email.</p> <p>“I want insights to show up everywhere,” he said, although he noted that will probably take a couple of years to achieve.</p> <p>He warned that data democratisation does come with risks. People can misinterpret data, cherry-pick conclusions (focusing on positives and ignoring negatives), or take material out of context – such as extrapolating a narrow customer survey to the general population. As a result, adequate training is critical.</p> <p>Sethi has been piloting the use of synthetic data – AI-generated responses based on the patterns and characteristics found in real-world data – since 2022. While its accuracy has risen to around 75%, he noted “there’s still a lot of optimism bias” because the underlying models have been trained to return more positive results than negative ones.</p> <p>In his trials, simple questions – such as those with yes/no answers or those querying brand awareness – can yield 90% to 95% accuracy. However, this falls with longer or more complex questions, or when trying to segment results by demographics such as gender or income. Qualtrics currently offers synthetic panels for the general US population, with plans to extend the capability to other countries and specific market segments.</p> <p>Ultimately, AI is accelerating research, not replacing it, Sethi said. It allows more data to be analysed faster and at a lower cost, helping researchers become more influential at the senior executive level.</p> <section class="section main-article-chapter" data-menu-title="Doing more with less at Fonterra"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Doing more with less at Fonterra</h2> <p>This idea of doing more at a lower cost and acting as a strategic partner to the C-suite was echoed by Tomasz Soluch, future insights solutions and partnership manager at New Zealand dairy cooperative Fonterra. “The business wanted to have more answers, more insights, more often,” he said.</p> <p>Because this was not possible using traditional agency-led research, Fonterra built an automated research engine using Qualtrics and supporting tools. Some teams use this platform on a self-service basis, though the traditional “do it for me” approach remains available for those requiring hands-on support.</p> <p>“We saved around NZ$1m, and around 30% in costs and time per project,” Soluch said. Teams in Oceania, Southeast Asia, China and the US are now running research projects within three to seven days. This achievement was recently recognised with an Esomar global award for excellence in AI and automation in market research.</p> <p>To improve the reuse of existing insights and reduce unnecessary repetition, the team created Insight Farm, a repository providing easy access to previous work.</p> <blockquote class="main-article-pullquote"> <div class="main-article-pullquote-inner"> <figure> Instead of seeing moments in isolation, we can now see how things connect, where friction starts, where it builds, and where it turns into a cost </figure> <figcaption> <strong>Siân Howatson, Swyftx </strong> </figcaption> <i class="icon" data-icon="z"></i> </div> </blockquote> <p>While the repository helped employees find what they were looking for, it didn’t necessarily help them answer specific questions, noted Tim Opie, general manager of front-end innovation and insights at Fonterra. As such, an AI-powered tool called DeepSights was built on top of Insight Farm to answer queries, generate summary reports and extract contextual data.</p> <p>Now, instead of emailing questions to the insights team, employees are opting for self-service. “Insight Farm unlocked our time” by handling 200 questions a month on its own, Soluch added.</p> <p>Another part of the insights team’s role is looking to the future by identifying emerging signals – not only from customer research, but from the wider world of science, technology and the company’s value chain. A custom-built Foresight tool does exactly that.</p> <p>Opie showed how a beta version of the software spotted growing interest in proactive ageing and longevity, identifying that the digestibility of small-molecule proteins (which can be delivered in milk products) could represent a commercial opportunity. The AI even suggested possible products, such as a “premium evening ritual mousse”. Such ideas can be stored in a database and automatically surfaced when market signals suggest the timing is right.</p> <p>With AI, the primary function of Fonterra’s insights team has shifted from project-managing outside agencies to focusing on overarching strategy and delivering business outcomes, Soluch said.</p> </section> <section class="section main-article-chapter" data-menu-title="Connecting the customer journey at Swyftx"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Connecting the customer journey at Swyftx</h2> <p>Elsewhere, crypto exchange Swyftx previously struggled to identify emerging patterns across various types of customer feedback before they impacted the business, according to its head of customer insights and automation, Siân Howatson. Because no single department had a complete view of the customer, “even when our teams were doing the right thing, patterns were really hard to spot”, she said.</p> <div class="pro-features-wrapper"></div> <p>To resolve this, Swyftx used Qualtrics to consolidate signals from 13 different feedback channels. “That’s given us something that we’ve never had before: a journey-level view of customer experience,” Howatson explained. “Instead of seeing moments in isolation, we can now see how things connect, where friction starts, where it builds and where it turns into a cost.”</p> <p>However, insight has no value unless it drives action. Swyftx’s Luma (Listen, Understand, Measure, Act) system connects these signals and analyses them through the lenses of revenue, cost, retention and risk. “Our goal is to make decisions, not just create more dashboards,” she added.</p> <p>Once an issue is identified, the team’s task is to find the smallest change that would improve matters, implement it and validate the results. For example, Swyftx spotted that a meaningful number of new customers were completing the verification process but failing to make their first trade within seven days. Broader data revealed the core problem: they simply did not know where to start. By adding a basic “what to do next” message to the onboarding process, the first-trade metric improved significantly and early support calls dropped.</p> <p>While the core insights team consists of just 1.5 full-time equivalent (FTE) staff, they are assisted by a group of 12 “Luma Legends” drawn from across the business – including engineering, marketing and customer support – who help interpret signals and identify appropriate operational changes.</p> <p>Swyftx also uses AI to identify top themes within customer feedback and has deployed an AI support agent capable of handling low-complexity, low-emotion enquiries, freeing up human support teams to deal with more complex issues.</p> <p>The company’s ultimate goal is to provide a proactive customer experience, anticipating needs rather than waiting for customers to ask for help. Howatson sees agentic AI playing a key role in achieving this, noting that one of the company’s guiding principles is: “Don’t automate around friction; remove it.”</p> <p>Howatson offered three tips for IT and CX leaders working in this area:&nbsp;</p> <ul type="disc" class="default-list"> <li><b>Start with business value, not just measurement</b>: Look for the smallest meaningful change you can make that will quickly demonstrate value.</li> <li><b>Consolidate existing feedback</b>: Most organisations already have enough customer feedback, but it needs to be brought together. You don’t need to consolidate everything at once – start small, show the value and iterate.</li> <li><b>Use AI to accelerate insights</b>: AI can make support more scalable and drive business value, but ensure you do not let the technology mask underlying structural problems.</li> </ul> </section> <section class="section main-article-chapter" data-menu-title="Empowering employee experience at CommBank"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Empowering employee experience at CommBank</h2> <p>While Qualtrics is highly visible in customer experience and market research, the supplier is increasingly serving the employee experience (EX) market.</p> <p>Perhaps its most prominent ANZ customer in the EX space is the Commonwealth Bank of Australia (CommBank). Matthew Hull, CommBank’s executive manager of culture and people experience insights, explained how the bank’s “listening and acting” experiments over the past three years have coincided with staff turnover falling from 14.8% to 8.4%. Employee engagement scores have remained close to the 90th percentile of Qualtrics’ global benchmarks, and CommBank recently achieved the highest-ever retail NPS score for a major Australian bank.</p> <p>Most organisations do not have a listening problem, but they do have an action problem. “They are drowning in data and listening without acting leads to the erosion of trust among employees,” Hull observed. “So, how do we act on what we already know?”</p> <p>Hull suggested that listening and acting should be embedded directly into the flow of work. “HR has always owned listening,” he said, but if business leaders and individual teams own the listening, they are far more likely to own the subsequent actions.</p> <p>To achieve this, CommBank has adopted a model of team-led listening, where anyone can initiate a survey, suggest questions and dictate the timing. The team subsequently receives an insight report and is encouraged to use it in their daily workflows, such as during daily stand-ups or sprint planning meetings.</p> <p>Behind the scenes, AI tools have helped accelerate pattern identification and comment analysis. This is critical for CommBank, whose annual employee survey yields upwards of 100,000 unique comments. A Qualtrics AI-powered feature that automatically generates follow-up questions during surveys has yielded significantly richer comments, while AI is also used to deliver tailored engagement insights to leaders at various levels of the business.&nbsp;</p> <p>“None of this replaces human judgement,” Hull noted, adding that all AI deployments are strictly managed within the bank’s frameworks for privacy and data governance. “It all goes back to trust.”</p> <p>While AI helps surface workplace issues faster, it remains up to human leaders to take the appropriate action, he concluded.</p> <div class="extra-info"> <div class="extra-info-inner"> <h3 class="splash-heading">Read more about AI in ANZ</h3> <ul class="default-list"> <li>Bunnings has gone from digital laggard to e-commerce pioneer, teaming up with Google Cloud to launch a&nbsp;<a href="https://www.computerweekly.com/news/366642113/Bunnings-shows-off-AI-shopping-agent-at-Google-showcase">conversational AI assistant</a>&nbsp;that turns simple queries into DIY project plans.</li> <li>Melbourne-based Heidi is building its own AI models and launching wearable hardware to automate documentation and&nbsp;<a href="https://www.computerweekly.com/news/366640992/Aussie-AI-health-tech-Heidi-aims-to-cure-clinical-burnout">reduce the administrative burden on doctors</a>.</li> <li>The Australian government has struck a major&nbsp;<a href="https://www.computerweekly.com/news/366639595/Australia-inks-five-year-deal-with-Microsoft-to-drive-AI-and-cloud-adoption">five-year volume sourcing agreement with Microsoft</a>&nbsp;to speed up adoption of AI and cloud technologies across the public sector.</li> <li>ANZ Bank has started&nbsp;<a href="https://www.computerweekly.com/news/366638802/ANZ-rolls-out-AI-agents-for-business-bankers">rolling out AI agents within its new CRM system</a>&nbsp;to help business bankers recover hours of lost productivity by automating tasks and streamlining workflows.</li> </ul> </div> </div> </section> At Qualtrics Experience Live in Sydney, leaders from Zip Co, Fonterra, Swyftx and Commonwealth Bank shared how AI is accelerating research, breaking down data silos and turning feedback into measurable business value https://cdn.ttgtmedia.com/visuals/German/article/Hero-Coding-peopleimages-com-15.jpg https://www.computerweekly.com/news/366642772/ANZ-enterprises-turn-to-AI-for-customer-and-employee-insights Mon, 04 May 2026 02:30:00 GMT <p>At the recent Zendesk Future of Service event in Sydney, Australian technology leaders provided a rare glimpse into how they are applying or preparing to <a href="https://www.computerweekly.com/news/366637110/AI-to-handle-four-in-10-customer-queries-in-Singapore-by-2027">apply artificial intelligence (AI) to customer service</a>.</p> <p>Along with the local case studies, Zendesk chief technology officer (CTO) Adrian McDermott revealed how the company is embedding AI into its products and revolutionising the software development process.</p> <section class="section main-article-chapter" data-menu-title="Solo by MYOB"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Solo by MYOB</h2> <p>MYOB’s new mobile-first product, Solo, emerged after research identified a glaring gap in the market for sole traders.</p> <p>“What we found was over half of them use spreadsheets to run their business; their books are all over the place,” said Sally Davies, general manager of Solo by MYOB.</p> <p>These business owners are ambitious but time-poor, driven by their craft rather than administration. Their business and personal lives are often intertwined, with 75% using personal bank accounts for business purposes – a habit that ironically makes their administration significantly harder.</p> <p>To address this, Solo pushes traditional accounting into the background, talking instead in terms of “money in” and “money out”. It incorporates financial services, including a bank account, so all of a sole trader’s admin work is centralised. This allows MYOB to apply AI to automate notoriously difficult tasks, such as end-of-month reconciliation, by automatically matching receipts and bank transactions.</p> <p>“So, we move from what was traditionally up to a five- or six-step process to one: take a snap at the receipt and you're done,” Davies said.</p> <p>However, even a model trained on invoices and receipts from hundreds of thousands of MYOB customers isn’t 100% accurate. When the AI’s confidence in a result falls below a certain threshold, the user is prompted to confirm or correct the interpretation.</p> <p>“We see so many invoices or receipts from Kmart because our customers will go there and buy kids’ shoes or toys as well as paper and pens and so on,” Davies said. “When we first started training the AI, it wasn’t great at the difference between business and personal.”</p> <p>In Solo’s early days, confirming the allocation between business and personal items was a core part of the workflow. As successive models became more accurate, that step has become the exception.</p> <p>Zendesk also became “a key part of our AI story”, Davies said, with MYOB’s community managers and support agents heavily involved in Solo’s design and development.</p> <p>“You don’t build a product and then go, ‘Oh, how do we support it?’” Davies explained. “You design a product in a way that service is a feature, and it changes from ‘What is the UX?’ or ‘What is the screen going to look like?’ to ‘What is that end-to-end experience going to look like?’”</p> <p>This digital-first, AI-first support model provides proactive guidance as users work through tasks, followed by a <a href="https://www.computerweekly.com/news/366629313/Zendesk-CTO-on-the-new-era-of-customer-experience">Zendesk-powered chatbot</a> that resolves 90% of remaining issues. That 10% failure rate is three to five times better than the industry standard, she noted, proving “the model that we use to design the product from the outset really is paying in dividends for both us and our customer”.</p> <blockquote class="main-article-pullquote"> <div class="main-article-pullquote-inner"> <figure> We’re in the early testing of an agentic AI coach for our members, providing general advice on financial literacy and so forth </figure> <figcaption> <strong>Richard Exton, Aware Super</strong> </figcaption> <i class="icon" data-icon="z"></i> </div> </blockquote> <p>While some industry surveys find a significant proportion of customers use a chatbot simply to bypass it and reach a human agent, Davies estimates this behaviour accounts for less than 1% of Solo users.</p> <p>The integration of financial services – such as online payments, tap-to-pay, and the bank account – remains an area where MYOB mandates human support, partly for compliance and partly to drive customer loyalty. But even here, AI assists as a “copilot” for community managers.</p> <p>Using Zendesk App Builder and marketplace integrations, MYOB created a custom app that aggregates customer-specific information from multiple sources, including app interactions and previous chatbot conversations. Notably, this was built not by an IT specialist, but by a community manager. Such projects can now go from an idea to a live capability in a week. “Ten years ago, it took you a week just to figure out who to have in the room [to discuss the project],” Davies said.<br>&nbsp;<br>This “service-as-a-feature” philosophy is now being extended to other MYOB products, including its Payday Super capability, which comes into effect on July 1.</p> </section> <section class="section main-article-chapter" data-menu-title="Guzman y Gomez"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Guzman y Gomez</h2> <p>AI is already live in the kitchens of several Guzman y Gomez (GYG) restaurants across Australia. Each kitchen operates two food preparation lines, and AI-based software now dynamically decides which line should prepare a new order. The goal is twofold: to deliver on the company’s “hotter, fresher, faster” mantra and to balance the load on crew members. This technology is part of an order management system (OMS) currently operating in nine restaurants, with a national rollout beginning in May.</p> <div class="pro-features-wrapper"></div> <p>There is significant potential to add more <a href="https://www.computerweekly.com/feature/Getting-started-with-agentic-AI">agentic AI workflows</a> to the system, according to GYG CTO Bryce Maybury. One concept under consideration is using AI to determine exactly when to open the second line, before the first becomes overwhelmed.</p> <p>It takes about 15 minutes to prep a line before it’s ready to serve food. “We’re going to analyse data at the edge in real time to determine when they should open a line, based on historic trends and the velocity of orders coming through,” Maybury said.</p> <p>This requires crunching complex data – including item modifications, order origins (point of sale, app, drive-through, or delivery aggregators), and the specific preparation time for each item at that location.</p> <p>“We know that by opening [the second line] even just 15 minutes earlier, that can have a huge impact on the guest experience and the time that a guest may wait,” Maybury explained, noting that saving even a few minutes is an important metric in the quick-service restaurant industry.</p> <p>Looking ahead, other data such as the weather or traffic conditions around drive-throughs might be added. “We haven’t started experimenting to see if they have any great impact. We know our restaurant managers, and they know their areas extremely well”, making stock and rostering decisions accordingly, Maybury said.</p> <p>The true role of machine learning in this space is still being tested to determine if it can genuinely outperform a human manager. Given there will always be a human running the kitchen, Maybury pondered whether an AI prediction would truly add value in every scenario.</p> <p>At a corporate level, GYG has been using tools such as Cursor and Claude Code to <a href="https://www.computerweekly.com/news/366639364/How-AI-code-generation-is-pushing-DevSecOps-to-machine-speed">develop software more quickly</a>. “At least 80% of our code is now generated by AI agents,” he said. The focus has been on identifying problems facing restaurants and then delivering new features and capabilities to them.</p> <p>As a long-term Zendesk customer, GYG uses the platform as its core tool for communicating with guests. It leverages Zendesk’s AI for classification, sentiment analysis and agent assistance. Future plans include an agentic system to automatically process Gomex Rewards claims for customers who forgot to scan their loyalty cards.</p> <p>“Guests just want their points as quickly as possible, and I’d rather our guest services team were dealing with real challenges and problems for customers rather than examining receipts and looking up the corresponding transaction,” Maybury said. “It's not technology for the sake of it. It actually has some benefits to both our guests and to our internal teams.</p> <p>“We know that there’s real opportunity to use [AI] for streamlining workflows inside our restaurants,” he added, noting that GYG is working on an agentic layer which will connect its internal systems, including a custom-built restaurant management system, to relieve crew workload.</p> <p>Later this year, the OMS will also gain a “cook to demand” feature, forecasting exactly when the next batch of chicken should be cooked to meet anticipated spikes in orders.</p> <p>“We see a future where we can streamline our operations and make life easier for our crew on the line, and to take out some of the cognitive load on our restaurant managers,” Maybury said.</p> <p>All of GYG’s head office staff – including those in IT – spend at least three days training and working in a restaurant as part of the induction process. “It gives you that grounding in what we do,” Maybury said.</p> <p>In addition, many of Maybury’s team have previously been employed as crew, cooks, shift leaders or restaurant managers, giving “unbelievable insights” into operations. That contact with the coalface continues, for example with the head of restaurant technology spending weeks in a restaurant during the development of the OMS to get feedback and making sure it worked as intended.</p> <p>“We exist to make the lives better for our restaurants and for our guests,” Maybury said. Over the coming year, the OMS will be rolled out across the country and more features and functions added, which should result in more efficient kitchens and better guest experiences.</p> </section> <section class="section main-article-chapter" data-menu-title="Aware Super"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Aware Super</h2> <p>For the financial services sector, agentic AI represents a chance to reimagine member servicing. Richard Exton, group executive and chief technology and data officer at Aware Super, sees an opportunity to provide high-value guidance that complements traditional human interaction.</p> <p>“We’re in the early testing of an agentic AI coach for our members, providing general advice on financial literacy and so forth,” Exton said. Early testing has revealed a surprising trend: some members feel more comfortable discussing their finances with an AI agent than a human.</p> <blockquote class="main-article-pullquote"> <div class="main-article-pullquote-inner"> <figure> Guests just want their points as quickly as possible, and I’d rather our guest services team were dealing with real challenges and problems for customers rather than examining receipts and looking up the corresponding transaction </figure> <figcaption> <strong>Bryce Maybury, Guzman y Gomez</strong> </figcaption> <i class="icon" data-icon="z"></i> </div> </blockquote> <p>Exton noted that Aware Super’s distinct advantages lie in its proprietary member data and its status as a trusted, regulated entity. While members are increasingly turning to free consumer tools such as <a href="https://www.techtarget.com/searchenterpriseai/tip/Pros-and-cons-of-ChatGPT-for-finance-and-banking">ChatGPT for financial advice</a>, these public models lack specific member context, regulatory backing and robust data protection. “Having that data, security, privacy and cultural development is key,” he said.</p> <p>One challenge he faced was ensuring that AI was approached from a whole organisation perspective, not as a specifically IT matter. This involved understanding the risks at a time when the regulators were still exploring them.</p> <p>Another was educating the staff. “It was all around getting the tools onto everybody’s desktop [and] setting up regular training, so people are not afraid to use these tools.”</p> <p>With the benefit of hindsight, Exton would have avoided jumping into proofs of concept. The starting point, he suggested, should be understanding the expected value that AI can provide in a particular context. Then the organisation – including the owners of that expected value – can decide whether it is worth investing in the project.</p> <p>He also warned against under-investing in governance, including data governance, and privacy for any organisation pursuing AI opportunities: “I think they go hand in hand, because you can have the best service out there, but as soon as you’re breached, your reputation is damaged, and no one will ever talk about how great your AI model is or what it’s worth.”</p> </section> <section class="section main-article-chapter" data-menu-title="Zendesk"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Zendesk</h2> <p>While using AI to automate repetitive support and sales conversations across chat, voice and email is now well-established, Zendesk’s McDermott believes the technology’s next frontier lies in supervision and preparatory work.<br>&nbsp;<br>A growing use case is deploying AI in a supervisory role. AI models can monitor all human agent conversations, scoring them on criteria ranging from poor grammar to inappropriate tone, and providing immediate coaching.<br>&nbsp;<br>Another is deploying long-running agents to complete preparatory work before a human ever sees a support ticket. These agents analyse text and attachments, interrogate backend systems to extract relevant data, and compile comprehensive notes for the human agent. “It’s very early days in that kind of technology,” McDermott said.<br>&nbsp;<br>AI is also driving continuous improvement. For instance, an AI agent might flag that 70% of human agents are modifying a specific automated response, or that customers are frequently calling about a new product missing from the company’s knowledge base. “We actually have a knowledge agent at Zendesk that does that,” he said.<br>&nbsp;<br>Internally, Zendesk is pushing the boundaries of agentic AI in software engineering. “We have more than a dozen teams who are using a pure agentic coding methodology” with zero human-written code, McDermott revealed. The productivity gains are staggering, with a single developer capable of managing a team of 20 AI agents.<br>&nbsp;<br>McDermott drew a parallel to the era when developers wrote in high-level languages but manually optimised certain portions in assembly code for speed. “Nobody does that anymore. You just trust the compiler,” he said.</p> <p>He predicted that the industry will soon treat <a href="https://www.computerweekly.com/feature/LLMs-explained-A-developers-guide-to-getting-started">large language models</a> (LLMs) as the compilers of our ideas. However, he warned that while AI coding tools are supposed to generate necessary software tests, recent research suggests some models will hallucinate passing tests just to fulfil their goals.</p> <p>The introduction of AI has dramatically widened the developer productivity gap. Engineers who were previously considered “10x” performers are now 50 times more productive using AI agents, while average engineers see only modest gains.</p> <p>“You shall know them not by their trail of code, but by their trail of features,” McDermott said. While a developer’s token consumption indicates their engagement with AI tools, the ultimate metric remains the value delivered to the business.<br>&nbsp;<br>Where programmers go today, all information workers will follow tomorrow, McDermott predicted, and this is about changing the focus from tasks to purposes – a contact centre worker has the task of handling enquiries from existing and prospective customers, but their purpose is to improve customer satisfaction and attract new ones.</p> <p>The technology also leads to a flattening of skill sets, he observed. For example, instead of a product manager writing a product requirements document, they generate prototypes in Lovable or Claude Code and there’s no need for the document. “It’s just such a richer way to present what’s going on,” McDermott said.</p> <div class="extra-info"> <div class="extra-info-inner"> <h3 class="splash-heading">Read more about AI in Australia</h3> <ul class="default-list"> <li>Bunnings has gone from digital laggard to e-commerce pioneer, teaming up with Google Cloud to launch a <a href="https://www.computerweekly.com/news/366642113/Bunnings-shows-off-AI-shopping-agent-at-Google-showcase">conversational AI assistant</a> that turns simple queries into DIY project plans.</li> <li>Melbourne-based Heidi is building its own AI models and launching wearable hardware to automate documentation and&nbsp;<a href="https://www.computerweekly.com/news/366640992/Aussie-AI-health-tech-Heidi-aims-to-cure-clinical-burnout">reduce the administrative burden on doctors</a>.</li> <li>The Australian government has struck a major&nbsp;<a href="https://www.computerweekly.com/news/366639595/Australia-inks-five-year-deal-with-Microsoft-to-drive-AI-and-cloud-adoption">five-year volume sourcing agreement with Microsoft</a>&nbsp;to speed up adoption of AI and cloud technologies across the public sector.</li> <li>ANZ Bank has started&nbsp;<a href="https://www.computerweekly.com/news/366638802/ANZ-rolls-out-AI-agents-for-business-bankers">rolling out AI agents within its new CRM system</a>&nbsp;to help business bankers recover hours of lost productivity by automating tasks and streamlining workflows.</li> </ul> </div> </div> </section> Local tech leaders from MYOB, Guzman y Gomez, and Aware Super reveal how AI is reshaping customer experience, streamlining business operations and driving efficiency https://cdn.ttgtmedia.com/visuals/German/HERO-KI-AI-714890654-machinelearning-Adobe-09.jpg https://www.computerweekly.com/news/366642624/How-Australian-firms-are-using-AI-in-customer-experience Mon, 04 May 2026 00:17:00 GMT <p>The potential use of <a href="https://www.computerweekly.com/resources/Artificial-intelligence-automation-and-robotics">artificial intelligence (AI)</a> to unleash cyber attacks at breakneck speeds is widening the asymmetry between threat actors and cyber defenders who still rely heavily on human oversight.</p> <p>That was according to Raghu Nandakumara, vice-president of industry strategy at <a href="https://www.computerweekly.com/news/366560912/APAC-organisations-warm-to-microsegmentation">microsegmentation</a> provider Illumio, who noted that while attackers are using AI tools to find vulnerabilities, weaponise exploits, and execute them at scale, cyber defenders remain cautious about letting automated systems take remediation actions.</p> <p>“The attacker side is always trying to automate as much as possible, because there’s no reason for them to have a human in the loop,” Nandakumara told Computer Weekly. Conversely, despite the availability of AI-powered security tooling, IT teams are hesitant to allow software to autonomously quarantine systems or take infrastructure offline without human verification.</p> <p>“They’re not confident that AI has enough context to be able to make the right decision, because it’s not aware of what the business impact is,” he added. “You can see that the asymmetry is only growing because the human is always going to put the brakes on.”</p> <section class="section main-article-chapter" data-menu-title="Assumed breach mindset"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Assumed breach mindset</h2> <p>Historically, organisations poured money into <a href="https://www.computerweekly.com/news/252468781/How-EDR-is-moving-beyond-the-endpoint">endpoint detection and response</a> (EDR) and perimeter firewalls, but those investments are no longer sufficient to deal with the machine speed of AI-powered adversaries.</p> <p>Instead, they must adopt an assumed breach mindset, Nandakumara said. “It’s not just the inevitability that cyber attacks are going to happen, but also the inevitability that a cyber attack – the initial intrusion into a target environment – will be successful.”</p> <p>That calls for security teams to build <a href="https://www.computerweekly.com/ehandbook/Cyber-resilience-under-pressure-How-to-demonstrate-readiness">cyber resilience</a>, so they can withstand an attack by limiting its blast radius and containing the breach – for instance, by applying granular microsegmentation at the network layer to trap an attacker who has bypassed perimeter controls.</p> <p>“Ultimately, the attacker is looking for some kind of vulnerability or misconfiguration to compromise so that they can get access to the network. If you better secure the network, you directly prevent or limit the attacker from moving around,” Nandakumara said.</p> <p>However, Nandakumara warned that security teams must clearly distinguish between microsegmentation as a technical capability and the policy outcomes they want to achieve. Granularity, whether separating individual ports and processes or simply isolating production from non-production environments, is simply a matter of policy, dictated by business risk.</p> </section> <section class="section main-article-chapter" data-menu-title="Complementing SASE and the modern security stack"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Complementing SASE and the modern security stack</h2> <p>While technologies such as <a href="https://www.computerweekly.com/news/365530168/APAC-buyers-guide-to-SASE">secure access service edge</a> (SASE) and <a href="https://www.computerweekly.com/opinion/Zero-trust-is-redefining-cyber-security-in-2025">zero trust network access</a> (ZTNA) have seen growing adoption, Nandakumara clarified that microsegmentation solves a fundamentally different problem.</p> <div class="pro-features-wrapper"></div> <p>He compared SASE services from cloud security suppliers such as Zscaler and Cloudflare to a building’s security guards. “They are essentially all focused on the front door. How do we take users that may be anywhere and securely connect them to your corporate environment?”</p> <p>Illumio, on the other hand, operates exclusively inside the perimeter. “How do we give you complete visibility and secure all of that connectivity within your building?” Nandakumara said, adding that the two approaches are complementary and necessary for a holistic zero-trust architecture.</p> <p>He also claimed that while cloud security suppliers have moved into the microsegmentation space, many have struggled due to underlying architectural limitations. “Desiring to take the same architectural approach and extending it to microsegmentation doesn’t necessarily work or is very difficult to do without introducing significant more complexity into the customer environment,” he said.</p> </section> <section class="section main-article-chapter" data-menu-title="OT convergence brings new segmentation demands"> <h2 class="section-title"><i class="icon" data-icon="1"></i>OT convergence brings new segmentation demands</h2> <p>Historically, operational technology (OT) networks that host industrial control systems and critical infrastructure lacked internet connectivity, making visibility and control difficult. However, as <a href="https://www.techtarget.com/searchitoperations/definition/IT-OT-convergence">OT and IT environments converge</a>, organisations are suddenly finding their OT systems exposed.</p> <p>According to Nandakumara, the market has changed dramatically in the past 18 months. What used to be a theoretical, “throwaway” question about whether OT segmentation was possible has now become a critical priority.</p> <p>“Through a combination of regulatory factors and modernisation of OT environments, we’re now starting to see a real focus on wanting to segment OT environments,” Nandakumara said.</p> <p>Whether it’s OT threats or AI agents, Nandakumara believes the core tenets of security remain the same – it is simply the scale and speed that are changing.</p> <p>“I don’t think cloud really introduced novel security challenges; it just made the same fundamental security things even more important, because everything was essentially one misconfiguration away from being exposed,” Nandakumara said. “It’s the same with AI, but on a scale and complexity we’ve not seen before.”</p> <div class="extra-info"> <div class="extra-info-inner"> <h3 class="splash-heading">Read more about cyber security in APAC</h3> <ul class="default-list"> <li>Singapore mobilised over 100 cyber defenders to neutralise a sophisticated APT actor which infiltrated Singtel, StarHub, M1 and Simba networks in the country’s <a href="https://www.computerweekly.com/news/366638973/Singapore-mounts-largest-ever-cyber-operation-to-oust-APT-actor">largest coordinated cyber incident response to date</a>.</li> <li>Japan’s Nikkei has confirmed a major data breach that potentially <a href="https://www.computerweekly.com/news/366634243/Nikkei-data-breach-exposes-personal-data-of-over-17000-staff">exposed the personal information of more than 17,000 employees</a> and business partners after hackers infiltrated its internal Slack messaging platform.</li> <li>Australian privacy commissioner warns that the <a href="https://www.computerweekly.com/news/366633983/Fewer-data-breaches-in-Australia-but-human-error-now-a-bigger-threat">human factor is a growing threat</a> as notifications caused by staff mistakes rose significantly even as total breaches declined 10% from a record high.</li> <li>Philippine bank <a href="https://www.computerweekly.com/news/366633428/BDO-Unibank-taps-Zscaler-to-secure-cloud-migration">BDO is shoring up its cyber security capabilities</a> to protect its data and systems as it moves more services to the cloud and expands its physical presence into remote areas of the archipelago.</li> </ul> </div> </div> </section> As threat actors leverage AI to launch attacks at machine speed, cyber defenders must adopt an assumed breach mindset and prioritise breach containment https://cdn.ttgtmedia.com/visuals/ComputerWeekly/Hero%20Images/network-security-padlock-businessman-adobe.jpeg https://www.computerweekly.com/news/366642503/AI-is-widening-the-asymmetry-between-attackers-and-defenders Thu, 30 Apr 2026 05:00:00 GMT <p>With <a href="https://www.computerweekly.com/news/366623023/How-AI-workloads-are-reshaping-datacentre-design">inferencing expected to account for the majority of artificial intelligence (AI) workloads</a> and the lower tolerance for latency, terrestrial datacentre infrastructure in India is facing severe constraints. That’s on top of <a href="https://www.techtarget.com/whatis/definition/data-sovereignty">data sovereignty</a> requirements across sectors such as defence, manufacturing, maritime and healthcare.</p> <p><a href="https://www.techtarget.com/searchdatacenter/feature/Space-based-data-centers-Edge-computing-in-space">Orbital datacentres</a> are emerging as a radical, yet increasingly viable, alternative to ground datacentres – even as establishing a presence in space comes with its own unique set of pros and cons.</p> <p>Consider the partnership between sovereign AI cloud infrastructure company NeevCloud and spacetech startup Agnikul Cosmos, announced in February 2026. The two firms have joined forces to launch India’s first indigenous AI-powered datacentre in space, with a pilot expected before the end of 2026. Other space startups, such as TakeMe2Space, are also looking to build orbital datacentres to run AI models directly on satellites.</p> <p>Reports suggest that the Department of Space (DoS) and the Indian Space Research Organisation (ISRO) are exploring the feasibility of placing physical datacentres in orbit to process and store satellite and communications data. But is this just another manifestation of edge computing, or something much bigger?</p> <section class="section main-article-chapter" data-menu-title="Why put datacentres in space?"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Why put datacentres in space?</h2> <p>For Narendra Sen, founder and CEO of NeevCloud, the case for orbital datacentres boils down to three irreplaceable advantages: energy, latency and sovereignty.</p> <p>“In space, you have unlimited access to solar power, and you can simply radiate excess heat into space,” said Sen. “None of the <a href="https://www.computerweekly.com/opinion/IT-Sustainability-Think-Tank-Rethinking-energy-communities-and-accountability-in-the-AI-era">water and energy problems that plague terrestrial facilities</a> exist up there. That is the clearest contrast with land-based datacentres, which are today shifting from carrier-neutral to power-neutral and carbon-neutral models because power has become the primary bottleneck.”</p> <p>Under the new partnership, Agnikul will provide the launch vehicle and orbital hosting platform using its extendable upper-stage rocket architecture, alleviating the need to build a dedicated satellite for orbital payloads.</p> <blockquote class="main-article-pullquote"> <div class="main-article-pullquote-inner"> <figure> In space, you have unlimited access to solar power, and you can simply radiate excess heat into space. None of the water and energy problems that plague terrestrial facilities exist up there </figure> <figcaption> <strong>Narendra Sen, NeevCloud</strong> </figcaption> <i class="icon" data-icon="z"></i> </div> </blockquote> <p>NeevCloud’s compute modules will leverage Agnikul’s platform, generating solar power in orbit and integrating AI chips directly within the architecture. Initial deployments are expected to consume around 10kW (kilowatts) to 15kW of power, with the potential to scale to 50kW, 200kW, or higher in future iterations.</p> <p>Moin SPM, Agnikul’s co-founder and chief operating officer, explained that terrestrial datacentres are fundamentally constrained because they must be built around population clusters and power grids. “They struggle to serve remote regions, moving assets, or applications needing global low-latency coverage. <a href="https://www.computerweekly.com/feature/Microsofts-underwater-datacentre-The-pros-and-cons-of-running-subsea-facilities">Underwater facilities solve cooling efficiently</a> but remain geography-bound and maintenance-heavy,” he said.</p> <p>Priya Krishnamurthy, director at Altos India, a subsidiary of Acer active in the localisation of AI servers for the Indian market, noted that orbital datacentres open up compelling possibilities, particularly in terms of access to near-limitless solar energy, reduced dependence on terrestrial infrastructure, and the ability to operate beyond geopolitical boundaries.</p> <p>“They can also significantly lower latency for certain satellite-based services and reduce land and water usage compared to traditional or underwater facilities,” she added.</p> <p>According to Sen, orbital datacentre nodes can deliver sub-15ms (millisecond) response times by reducing the physical distance between compute and users, compared to the general round-trip latency of 100ms to 200ms for terrestrial datacentres. “No underwater facility can match that for globally distributed, real-time AI inference,” he said.</p> <p>There’s also a broader strategic element at play. Punit Badeka, co-founder of EON Space Labs, noted: “The next war is going to be a space war. Space is the place where the next strategic significance lies, and countries will need to match infrastructure and strengths up there.”</p> </section> <section class="section main-article-chapter" data-menu-title="Redefining PUE"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Redefining PUE</h2> <p>If orbital datacentres are to compete with their on-ground counterparts, traditional metrics like <a href="https://www.techtarget.com/searchdatacenter/definition/power-usage-effectiveness-PUE">power usage effectiveness (PUE)</a> must be completely rethought.</p> <div class="pro-features-wrapper"></div> <p>“PUE was designed for a world where power, cooling and land were relatively predictable inputs,” said Sen. “In the AI era, we are already seeing its limitations: rack densities have moved from 8-10kW to 100-150kW. A space datacentre, powered entirely by solar and with no mechanical cooling overhead, would structurally achieve PUE figures closer to 1.0 – essentially all power goes to compute. That is theoretically superior to even the best terrestrial facilities.”</p> <p>Operating from orbit could also reduce the need for multiple replicated terrestrial edge datacentres, cutting graphics processing unit (GPU) duplication, capital expenditure, land use and cooling infrastructure.</p> <p>However, the environmental footprint of launching datacentre systems into space remains a major consideration. “We are clear-eyed about the launch footprint,” Sen admitted. “The environmental impact of launches needs to be addressed, and deployment consumes Earth resources that cannot be recovered. Agnikul’s convertible upper-stage model partially addresses this by repurposing hardware that would otherwise become debris.”</p> </section> <section class="section main-article-chapter" data-menu-title="Engineering and maintenance challenges"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Engineering and maintenance challenges</h2> <p>The challenges facing space-based compute are not trivial. Building an orbiting datacentre means tackling radiation, component degradation, thermal management in a vacuum, limited maintenance, and a connectivity chain reliant on space links and ground stations, said Sen.</p> <p>There’s also the problem of cooling. On Earth, heat dissipates mostly through convection – via air or water – a process that simply does not exist in the vacuum of space. That said, Krishnamurthy believes the absence of atmospheric heat in space and the availability of continuous solar energy reduce the need for traditional cooling infrastructure.</p> <p>“However, thermal management doesn’t disappear; it simply becomes a design challenge involving radiative cooling and heat dissipation in a vacuum, which requires highly specialised engineering,” she added.</p> <p>Also, unlike terrestrial or underwater facilities, human intervention is near-impossible, making maintenance of orbital datacentre systems and satellites difficult. “Repairs or upgrades would be infrequent, complex and expensive, often relying on robotics or future in-orbit servicing capabilities,” noted Krishnamurthy.</p> <p>As such, operators are looking at hardware refreshes rather than field servicing. “Repairing a satellite in space would likely cost more than launching a replacement,” Sen admitted. “Instead, the plan is to de-orbit any failed or outdated module and replace it. The satellite will be intentionally withdrawn and safely de-orbited at the end of its lifecycle. It’s closer to how we think about consumer electronics than traditional datacentre operations.”</p> <p>Agnikul’s Moin SPM is confident that the operational challenges of space datacentres can be overcome. “Radiation hardening, autonomous operation and debris mitigation are established design disciplines. Building for space demands rigour from day one, and that rigour is precisely what separates credible orbital infrastructure from conceptual proposals,” he said.</p> </section> <section class="section main-article-chapter" data-menu-title="The use case for orbital inference"> <h2 class="section-title"><i class="icon" data-icon="1"></i>The use case for orbital inference</h2> <p>When space datacentres come online, their primary function will be AI inferencing, not training.</p> <p>“Inference accounts for 10 times the demand once training is done,” Sen noted. “The planned infrastructure supports latency-sensitive defence systems, unmanned vehicles, border surveillance and remote healthcare use cases.”</p> <blockquote class="main-article-pullquote"> <div class="main-article-pullquote-inner"> <figure> Over 80% of the world's population lives more than 200ms away from the nearest AI datacentre, rendering real-time applications like autonomous driving, remote robotic surgery, and industrial automation unreliable in vast regions of the Global South. To truly democratise AI, we must decouple it from terrestrial limitations </figure> <figcaption> <strong>Narendra Sen, NeevCloud</strong> </figcaption> <i class="icon" data-icon="z"></i> </div> </blockquote> <p>Processing data directly in space makes sense for Earth observation platforms, which generate huge volumes of data that are more efficiently analysed in orbit than downlinked to Earth in full. “Real-time AI inference for remote environments, vessels, aircraft and disaster zones needs compute access that ground infrastructure cannot deliver without meaningful delay,” added Moin SPM.</p> <p>For governments and defence organisations, the appeal of highly secure, sovereign data processing isolated from geopolitical disruptions is compelling. Badeka said domestically controlled space infrastructure will reduce India’s reliance on foreign satellite imagery for sectors like agriculture, empowering users with real-time, actionable advice.</p> </section> <section class="section main-article-chapter" data-menu-title="Timeline and market potential"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Timeline and market potential</h2> <p>The pilot launch for NeevCloud’s project is scheduled before the end of 2026, with an ambitious aim to scale to more than 600 orbital edge datacentres over the next three years.</p> <p>Moin SPM described the current phase as a critical proof-of-concept. “We are validating the architecture, power systems and data pipeline before scaling. The longer-term goal is a distributed fleet of modular platforms in orbit.”</p> <p>For Sen, the project is much more than a one-off experiment. “Over 80% of the world’s population lives more than 200ms away from the nearest AI datacentre, rendering real-time applications like autonomous driving, remote robotic surgery, and industrial automation unreliable in vast regions of the Global South. To truly democratise AI, we must decouple it from terrestrial limitations.”</p> <p>Sen estimates the space datacentre sector could be worth $3bn to $5bn over the next two to three years, eventually swelling to a $50bn global market by 2040.</p> <p>“India’s positioning is intentional,” said Sen. “This is not just about building infrastructure; it is about ensuring that the next decade of global AI intelligence – from village health posts to border surveillance – does not depend on foreign compute that can simply be switched off.”</p> <div class="extra-info"> <div class="extra-info-inner"> <h3 class="splash-heading">Read more about IT in India</h3> <ul class="default-list"> <li>Nvidia unveils&nbsp;<a href="https://www.computerweekly.com/news/366639266/Nvidia-backs-Indias-sovereign-AI-push-with-gigawatt-scale-infrastructure">compute expansion with L&amp;T, Yotta and E2E Networks</a>&nbsp;at the India AI Impact Summit, paving the way for domestic heavyweights to build AI agents and physical AI applications.</li> <li>While&nbsp;<a href="https://www.computerweekly.com/news/366639543/India-AI-Impact-Summit-Open-source-gains-ground-but-sovereignty-tensions-persist'">open source AI gained unprecedented recognition</a>&nbsp;during the India AI summit, divisions over governance, market concentration and regulatory power cast doubt on whether the technology will benefit society as a whole.</li> <li>Krutrim, the AI venture from Indian ride-hailing and EV giant Ola, is building a&nbsp;<a href="https://www.computerweekly.com/news/366629172/Olas-Krutrim-builds-AI-first-sovereign-cloud-for-India">vertically integrated sovereign cloud and AI stack for India</a>&nbsp;using Cloudera’s data platform as a core component of its architecture.</li> <li>OpenAI is preparing a&nbsp;<a href="https://www.computerweekly.com/news/366630088/OpenAI-targets-India-with-datacentre-push">one-gigawatt datacentre in India</a>&nbsp;as part of its $500bn Stargate infrastructure push, in what would be its biggest bet yet on its second-largest user base.</li> </ul> </div> </div> </section> As terrestrial datacentres face severe power and cooling constraints, space-based facilities promise unlimited solar energy and low latency for AI inferencing, provided the industry can overcome challenges https://cdn.ttgtmedia.com/visuals/ComputerWeekly/Hero%20Images/Space-hero-AdobeStock_393796896.jpg https://www.computerweekly.com/news/366642407/India-aims-for-the-stars-with-orbital-datacentres Thu, 30 Apr 2026 04:42:00 GMT <p>In the near future, your newest colleague might not be human. But it will still have its own email address, a dedicated software license, and perhaps even its own corporate credit card.</p> <p>That is the vision of Roy Mann, CEO of work management software company <a href="https://www.computerweekly.com/news/366633675/Mondaycom-eyes-ASEAN-growth-with-the-Singapore-hub">Monday.com</a>, which has launched its <a href="https://app.globster.ai/">Globster service</a>, allowing consumers and businesses to harness the capabilities of <a href="https://www.computerweekly.com/feature/Moving-agentic-AI-from-innovation-theatre-to-enterprise-production">agentic artificial intelligence</a> (AI).</p> <p>Conceived by the company’s Agent Labs division, Globster is built on the <a href="https://www.computerweekly.com/news/366640697/Why-OpenClaw-agents-are-the-next-big-enterprise-challenge">open-source OpenClaw framework</a> but wrapped in <a href="https://www.techtarget.com/searchitoperations/news/366640420/Nvidia-NemoClaw-JFrog-shore-up-OpenClaw-security">Nvidia’s NemoClaw infrastructure</a>. The service aims to democratise access to AI agents by removing the technical friction and security risks typically associated with deploying them.</p> <p>In an interview with Computer Weekly, Mann noted that the tech industry is entering the third wave of AI, characterised by AI agents that can reflect and adapt to new circumstances, going beyond chatbots and structured agentic behaviours in the first and second waves. “They don’t just do things – they can understand what they did, change and improve themselves,” he said.</p> <p>Mann said the third wave of AI has prompted Monday.com to transform its company vision “from managing work to doing the work, and agents obviously are a massive part of it”.</p> <p>While open-source projects like OpenClaw have seen <a href="https://www.computerweekly.com/news/366640697/Why-OpenClaw-agents-are-the-next-big-enterprise-challenge">viral adoption</a>, deploying them requires dedicated hardware, <a href="https://www.computerweekly.com/feature/Enterprise-strategies-for-API-management">application programming interface</a> (API) keys, and advanced technical knowledge. Globster aims to ease adoption by providing a fully hosted, consumer-friendly interface. “It’s a self-serving, one-click OpenClaw service,” said Mann.</p> <p>Under the hood, Globster provisions a dedicated virtual machine for a user’s agent in about two minutes. And instead of forcing users to bring their own API keys from various AI providers, Globster handles the backend keys natively. Users can select their preferred <a href="https://www.computerweekly.com/feature/LLMs-explained-A-developers-guide-to-getting-started">large language model</a>&nbsp;(LLM) based on its intelligence level and price per million tokens, paying via a credit-based monthly subscription that starts at $23 for an annual plan.</p> <p>Once deployed, the agent can connect to standard workplace tools, including Gmail, Google Calendar, Google Drive, WhatsApp and Slack. The platform offers granular data controls, allowing users to define exactly what the agent can and cannot access. Users can also tweak their agent’s core underlying system files, adjusting its identity, conversational tone, avatar and background knowledge, so the agent adapts to their personal working style.</p> <section class="section main-article-chapter" data-menu-title="Security and enterprise governance"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Security and enterprise governance</h2> <p>Granting an AI agent autonomy over an inbox or calendar poses privacy and security risks, which Monday.com is addressing through a partnership with Nvidia.</p> <p>“The infrastructure for Globster is NemoClaw,” said Mann, referring to Nvidia’s secure runtime environment for AI agents. “We are working with Nvidia and contributing to the project to provide the best security.”</p> <p>For corporate deployments, Monday.com is preparing an enterprise-grade tier. This will allow IT departments to deploy fleets of OpenClaw agents across an organisation in a single click, while retaining strict control over governance.</p> <p>Administrators will also be able to allocate agents to employees, enforce usage policies, set budget limits and strictly limit what software can be installed on the agents’ virtual machines. Monday.com is even partnering with financial platform Mesh to allow businesses to issue corporate credit cards with spending limits to AI agents.</p> <p>As AI agents become capable of performing the work of human employees, some industry analysts have questioned whether traditional <a href="https://www.computerweekly.com/resources/Software-as-a-Service-SaaS">software-as-a-service</a> (SaaS) per-seat pricing models will collapse.</p> <p>Mann dismissed such concerns, arguing that AI agents will instead act as revenue multipliers. “What we are going to see is seats going up, because people will invite external agents which need seats,” he said.</p> <p>In fact, Mann expects a windfall for software companies that successfully adapt to the agentic era. “The budget for software is going to increase dramatically,” he said. “Customers are going to be willing to spend way more money on this technology, because it empowers them.</p> <p>“Those that don’t make the change and transform will not make it,” said Mann. “There is a massive opportunity out there and I think it’s a great time for software.”</p> <div class="pro-features-wrapper"></div> <div class="extra-info"> <div class="extra-info-inner"> <h3 class="splash-heading">Read more about AI in APAC</h3> <ul class="default-list"> <li>Agoda, a digital travel platform, has set its sights on&nbsp;<a href="https://www.computerweekly.com/news/366640804/Agoda-scales-AI-strategy-opens-new-APAC-tech-hub">becoming an AI-powered travel companion</a>&nbsp;as it changes how it builds software and moves its tech workforce into a new facility in Bangkok.</li> <li>Singtel and Nvidia have teamed up on a multimillion-dollar facility to&nbsp;<a href="https://www.computerweekly.com/news/366639492/Singtel-Nvidia-to-help-scale-enterprise-AI-deployments">help organisations scale enterprise AI deployments</a>, tackle extreme datacentre power densities, and prepare for the era of embodied AI.</li> <li>The Australian government has struck a&nbsp;<a href="https://www.computerweekly.com/news/366639595/Australia-inks-five-year-deal-with-Microsoft-to-drive-AI-and-cloud-adoption">five-year volume sourcing agreement with Microsoft</a>&nbsp;to speed up adoption of AI and cloud technologies across the public sector.</li> <li>Alibaba Group has unveiled&nbsp;<a href="https://www.computerweekly.com/news/366640461/Alibaba-joins-AI-agent-race-with-Wukong-launch">Wukong</a>, an AI-native enterprise platform that brings advanced agentic AI capabilities directly into business workflows.</li> </ul> </div> </div> </section> The work management software firm’s Globster service brings OpenClaw to consumers and businesses in a bid to democratise access to agentic AI capabilities https://cdn.ttgtmedia.com/visuals/ComputerWeekly/HeroImages/lobster-cooked-red-food-bajita111122-adobe.jpg https://www.computerweekly.com/news/366642592/Mondaycom-targets-third-wave-of-AI-with-OpenClaw-service Wed, 29 Apr 2026 02:27:00 GMT <p>After years of pilots and prototypes, AI is finally <a href="https://www.computerweekly.com/news/366627053/Enterprise-AI-adoption-moving-beyond-experimentation">moving from experimentation to daily operations</a> across Southeast Asia. But as businesses accelerate adoption, a new question emerges: can enterprise AI truly scale on yesterday’s networks?</p> <p>Singapore’s Budget 2026 reinforced this shift in thinking, with the launch of a new National AI Council chaired by prime minister Lawrence Wong with <a href="https://www.computerweekly.com/news/366638920/Singapore-to-form-National-AI-Council-expands-tax-breaks-to-ease-AI-adoption">sector‑specific AI missions</a> and a Champions of AI programme for companies ready to transform. As AI use cases move deeper into factories, hospitals, branches and retail floors, many organisations are discovering that their wireless infrastructure, not their models, is the real test of readiness.</p> <p>Across Southeast Asia, we see AI embedded in day‑to‑day workflows: from predictive analytics in logistics and ports, to computer vision in smart retail and AI‑assisted quality inspection on manufacturing lines. In healthcare, hospitals are piloting AI‑supported triage, imaging analysis and bed‑management tools, all of which rely on timely data flows within and beyond the campus.</p> <p>But as these use cases mature, the operational expectations placed on the network begin to shift. AI systems depend on continuous data exchange between devices, edge computing nodes and cloud platforms in real time. This means networks must handle far more connected devices, time-sensitive data and deliver greater bandwidth in complex, high-density environments. In many cases, the network becomes the limiting factor in how effectively AI can operate at scale.</p> <p>As AI ambitions rise faster than network capabilities, the question is no longer <i>what</i> AI can, but whether infrastructure can keep up.</p> <section class="section main-article-chapter" data-menu-title="AI is changing the demands on enterprise networks"> <h2 class="section-title"><i class="icon" data-icon="1"></i>AI is changing the demands on enterprise networks</h2> <p>Traditional <a href="https://www.computerweekly.com/news/366623768/Wi-Fi-7-trials-show-significant-performance-gains-in-enterprise-environments">enterprise Wi‑Fi</a> was built around human‑centric, best‑effort connectivity: email, collaboration tools and periodic large file transfers. Even as organisations upgraded to Wi‑Fi 5 and Wi‑Fi 6, many network designs were still anchored in providing coverage and acceptable average throughput per user in office and campus settings. Now, AI‑driven operations are reshaping assumptions about what reliable, high-performance connectivity needs to look like in three important ways.</p> <p>Latency and jitter, once considered purely technical metrics, are increasingly becoming business concerns. A video call may tolerate brief fluctuations in connectivity, but systems such as computer vision monitoring worker safety, fraud‑detection engines in financial services or clinical decision support tools in hospitals cannot afford intermittent delays and dropped packets without eroding trust in the system.</p> <p>At the same time, the number of connected devices within enterprise environments is rising sharply. Where a traditional office network may have supported a few hundred laptops and smartphones, a modern plant or smart building can host thousands of connected sensors, cameras and actuators. Each continuously generates or consumes data that feeds into AI models in real time, dramatically increasing the load placed on wireless infrastructure.</p> <p>Traffic patterns are also becoming far more dynamic, especially when models are retrained or synchronised across edge, core and cloud. These processes can generate bursts of large data transfers — such as video datasets from cameras or model updates distributed across multiple sites — creating sudden spikes in network demand. When these characteristics collide with legacy Wi‑Fi designs built for lighter, human-driven usage, the strain becomes quickly visible: buffering in augmented reality/virtual reality‑based training environments, gaps in video analytics feeds, inconsistent telemetry for predictive maintenance systems or time‑outs in AI‑driven customer‑facing applications.</p> <p>The business impact is not just slower networks; it is stalled productivity and frustrated users.</p> </section> <section class="section main-article-chapter" data-menu-title="Wi‑Fi 7 as the backbone of enterprise AI"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Wi‑Fi 7 as the backbone of enterprise AI</h2> <p>This is where Wi‑Fi 7 starts to matter as part of the digital backbone for AI. <a href="https://wballiance.com/resource/wi-fi-7-trials-for-enterprise-scenarios-tt-commscope-and-intel/">Real‑world trials by the Wireless Broadband Alliance</a> have demonstrated significant performance gains for enterprise scenarios, including higher throughput, better efficiency and lower latency than previous generations.</p> <div class="pro-features-wrapper"></div> <p>Under ideal laboratory conditions, Wi‑Fi 7 has achieved theoretical speeds of up to 46 Gbps – nearly five times the upper limit of Wi‑Fi 6 – with dramatic reductions in latency for seamless, real‑time connectivity. This is good news for AI content and models that must be refreshed frequently across multiple sites. In practical terms, Wi-Fi 7 can shrink the time needed to distribute a 100GB 4K training or simulation file from minutes to seconds, enabling faster deployment of AI models, updates and applications across distributed environments.</p> <p>Equally important are features such as multi‑link operation (MLO), enhanced spectral efficiency and improved interference management. MLO allows devices to use multiple bands concurrently, increasing resilience and reducing the risk of congestion on a single channel disrupting a critical workload. In dense environments such as factories and logistics hubs, Wi‑Fi 7’s capacity and ability to serve large numbers of concurrent devices make it a strong candidate for industrial IoT and real‑time analytics indoors, alongside private 5G outdoors.</p> </section> <section class="section main-article-chapter" data-menu-title="From back‑end IT upgrade to board‑level enabler"> <h2 class="section-title"><i class="icon" data-icon="1"></i>From back‑end IT upgrade to board‑level enabler</h2> <p>Singapore’s new National AI Council and the associated AI missions make clear that connectivity is now part of the country’s AI strategy. It is explicitly named as one of four focus sectors, alongside advanced manufacturing, finance and healthcare, reinforcing that networks sit at the heart of AI‑enabled transformation rather than at the edge. The Champions of AI programme, targeted at firms looking to comprehensively transform their businesses with AI, will further encourage companies to rethink the robustness of their digital foundations.</p> <p>In this context, treating Wi‑Fi 7 as a routine IT refresh misses the point. For many organisations in Singapore and across Southeast Asia, the decision to modernise wireless infrastructure is now tightly linked to questions boards are asking about productivity, customer experience and resilience. For instance: Can our hospitals safely rely on AI‑supported workflows if clinical devices and applications share congested Wi‑Fi with general traffic? Can our branches and retail outlets deliver personalised, AI‑driven experiences consistently across markets in the region, or will performance vary depending on local network limitations?</p> <p>These are strategic rather than purely technical questions. They require a clear view of spectrum, architecture, security, edge computing and how Wi‑Fi 7 will interoperate with existing Wi‑Fi and <a href="https://www.computerweekly.com/news/366638797/Private-LTE-5G-networks-reached-6500-deployments-in-2025">private 5G deployments</a> over the next decade.</p> <p>Ultimately, as AI becomes embedded in everyday operations, the conversation around network upgrades is shifting from infrastructure maintenance to business enablement — setting the stage for CIOs and COOs to rethink how connectivity investments support their organisation’s broader AI ambitions.</p> </section> <section class="section main-article-chapter" data-menu-title="Practical considerations for CIOs and chief operating officers"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Practical considerations for CIOs and chief operating officers</h2> <p>As enterprises plan their next generation of wireless infrastructure, a few considerations can help align Wi‑Fi 7 investments with AI ambitions.</p> <ul class="default-list"> <li><b>Anchor network design on AI</b><b>‑</b><b>critical workflows.</b> Identify which applications are most sensitive to latency, jitter and downtime and ensure that Wi‑Fi 7 architectures and policies explicitly protect these workloads.</li> <li><b>Plan for coexistence and evolution. </b>Most organisations will not replace their entire installed base of devices or networks overnight. Wi‑Fi 7 will need to work alongside earlier Wi‑Fi generations and, in many cases, private 5G. Clear segmentation, roaming and security policies across these domains help avoid blind spots and inconsistent user experiences.</li> <li><b>Choose partners who understand both connectivity and the local AI context.</b> In Southeast Asia, regulatory frameworks, spectrum availability, building typologies and industry structures vary significantly by market. Working with providers who have experience designing networks for local conditions can help ensure that Wi‑Fi 7 deployments are not just technically robust, but strategically aligned.</li> </ul> <p>As Singapore advances its AI ambitions, the enterprises that will benefit most are those that recognise their wireless foundation as a core part of their AI strategy. While Wi‑Fi 7 is not a silver bullet, it is a critical piece of the puzzle, ensuring AI systems designed in boardrooms and innovation labs can perform reliably on-ground.</p> <p><i>Mustafa Kapasi is chief operating officer of M1</i></p> </section> Enterprises are quickly discovering that their wireless infrastructure is the real barrier to AI readiness. To achieve true transformation, it is time to stop relying on legacy networks and treat Wi-Fi 7 as a business enabler https://cdn.ttgtmedia.com/visuals/ComputerWeekly/Hero%20Images/wi-fi-abstract-jijomathai-adobe.jpg https://www.computerweekly.com/opinion/Can-enterprise-AI-in-Singapore-succeed-without-WiFi-7 Thu, 23 Apr 2026 20:51:00 GMT <p>Singapore grocery and retail giant FairPrice Group (FPG) is expanding its <a target="_blank" href="https://www.computerweekly.com/resources/Artificial-intelligence-automation-and-robotics" rel="noopener">artificial intelligence</a> (AI)-powered innovations to supermarkets across Singapore by the end of 2026.</p> <p>Developed in collaboration with Google Cloud, the nationwide roll-out will introduce consumer-facing upgrades such as smart shopping carts and digital price cards, along with an artificial intelligence (AI-)powered Grocer Genie app designed to streamline operations for frontline workers.</p> <p>The move follows a successful pilot of the <a target="_blank" href="https://www.computerweekly.com/news/366625453/FairPrice-taps-Google-Cloud-for-AI-powered-store" rel="noopener">Store of Tomorrow programme</a> at the FairPrice outlet in Punggol Digital District, which launched in August 2025.</p> <p>By the end of 2026, 48 FairPrice Xtra and Finest outlets will be equipped with smart carts. Integrated with Google Cloud’s Gemini Enterprise Agent Platform, these carts act as personal shopping assistants, helping customers navigate aisles, offering personalised promotions, and allowing shoppers to scan and pay on the go. According to FPG, the smart carts have successfully reduced average checkout times from several minutes to just 36 seconds.</p> <p>Vipul Chawla, group CEO of FairPrice Group, said the expansion aims to remove the friction from weekly grocery runs: “By bringing proven AI solutions from our Store of Tomorrow programme to more supermarkets across the island, we want to reimagine the shopping experience for our customers</p> <p>“Whether it’s with smart carts that provide personalised offers and in-store navigation or hybrid retail formats that bring together the best of physical and online shopping, our aim with the programme is to make every day a little better for all in Singapore.”</p> <section class="section main-article-chapter" data-menu-title="Listening to customer feedback"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Listening to customer feedback</h2> <p>The islandwide expansion is the culmination of rigorous testing and customer feedback. During a media briefing at Google Cloud Next 2026 in Las Vegas, Miguel Ho, FPG’s head of process automation, shared that shopper input directly influenced the evolution of the smart cart’s design.</p> <p>Initially, the pilot featured a unibody cart that could not be pushed out of the store, frustrating shoppers who wanted to wheel their groceries directly to the taxi stand or car park.</p> <p>“Having heard that, we went back to the drawing board,” Ho explained. “Over the next three months, we re-engineered a new prototype featuring a removable tablet. It allows customers, after their shopping journey is complete, to remove the tablet and then push the trolley into the car park.”</p> <p>Beyond improving the customer experience, a core focus of the tech roll-out is improving the daily lives of FairPrice’s frontline workforce.</p> <p>Currently, store employees juggle up to 50 different handheld applications to complete various tasks. By the end of 2026, all supermarket store teams will be equipped with Grocer Genie, a consolidated AI-powered app, which FPG’s chief digital and technology officer, Dennis Seah, described as the staff's “new friend, new agent and new sidekick”.</p> <p>Hui Hui Voon, FairPrice’s head of front office solutions, noted that the app shifts the burden of task management from the employees to the AI. “Instead of having the mental build-out of exactly what they have to do today or tomorrow, relying on PDAs [personal digital devices], paper or email, we have everything powered through the mobile device,” she said.</p> <p>Voon added that the app will integrate with in-store video analytics: “When there is a stock-out scenario, the video analytics will know exactly when it happens and trigger a notification to our staff for them to replenish accordingly.”</p> <p>For branch managers such as Sarah Jane Vasquez at the Punggol Digital District store, the AI assistant has already changed her daily routine. “New digital tools like Grocer Genie help me automate manual work like eyeballing when shelves need to be restocked, and even staff rostering. This frees up time for me to lead and coach my team,” she said.</p> <p>Other innovations rolling out to 48 outlets by 2026 include digital price cards, which provide real-time pricing while eliminating the need for printed paper tags. FPG projects this will save 15,000 man-hours and $138,000 annually. The group is also expanding its ShopBeyond format, which lets in-store shoppers scan physical displays to purchase related online catalogue items for home delivery.</p> <p>Looking ahead, FPG hinted that its technological transformation won’t stop at software. When asked about the future of automated supermarkets, Seah noted that moving from agentic AI to robotics is the next natural evolution. The company is already exploring ways to help older employees with heavy lifting and shelf-stocking, ensuring that technology continues to serve both the consumer and the worker.</p> <p>“We always believe that the customer experience will never exceed that of the staff experience,” Seah said. “As we work on the customer experience journey using technology, we need to have just as many initiatives for our frontline staff so that they can free themselves to influence the journey for the customer.”</p> <div class="pro-features-wrapper"></div> <div class="extra-info"> <div class="extra-info-inner"> <h3 class="splash-heading">Read more about AI in ASEAN</h3> <ul class="default-list"> <li>Agoda, a digital travel platform, has set its sights on&nbsp;<a href="https://www.computerweekly.com/news/366640804/Agoda-scales-AI-strategy-opens-new-APAC-tech-hub">becoming an AI-powered travel companion</a>&nbsp;as it changes how it builds software and moves its tech workforce into a new facility in Bangkok.</li> <li>Singtel and Nvidia have teamed up on a multimillion-dollar facility to&nbsp;<a href="https://www.computerweekly.com/news/366639492/Singtel-Nvidia-to-help-scale-enterprise-AI-deployments">help organisations scale enterprise AI deployments</a>, tackle extreme datacentre power densities, and prepare for the era of embodied AI.</li> <li>Malaysia’s&nbsp;<a href="https://www.computerweekly.com/news/366634082/Ryt-Bank-taps-agentic-AI-for-conversational-banking">Ryt Bank is using its own LLM and agentic AI framework</a>&nbsp;to allow customers to perform banking transactions in natural language, replacing traditional menus and buttons.</li> <li>Google Cloud has officially&nbsp;<a href="https://www.computerweekly.com/news/366637529/Google-Cloud-opens-Bangkok-region-to-support-Thailands-AI-economy">launched its first cloud region in Thailand</a>, fulfilling the company’s&nbsp;<a href="https://www.computerweekly.com/news/366612452/Google-invests-1bn-in-Thailands-cloud-future">pledge to invest $1bn</a>&nbsp;in building its cloud and datacentre infrastructure in the country.</li> </ul> </div> </div> </section> Shoppers can expect smart carts that slash checkout times to just 36 seconds, while supermarket staff will get an AI sidekick to automate daily operations https://cdn.ttgtmedia.com/visuals/LeMagIT/hero_article/Supermarket.jpg https://www.computerweekly.com/news/366642213/FairPrice-to-roll-out-AI-powered-smart-carts-to-more-stores Thu, 23 Apr 2026 19:20:00 GMT <p>Australian hardware chain Bunnings took centre stage at Google Cloud Next 2026 this week as it showed off Buddy, an <a href="https://www.computerweekly.com/resources/Artificial-intelligence-automation-and-robotics">artificial intelligence</a> (AI)-powered shopping assistant that provides customers with expert advice and helps them find what they need.</p> <p>The move comes as retail e-commerce is moving away from traditional search towards <a href="https://www.techtarget.com/searchcustomerexperience/feature/What-agentic-commerce-means-for-CXOs-and-B2B-buying">agentic commerce</a>, where virtual agents have reasoning capabilities to understand context, identify complex needs, and act on behalf of the customer.</p> <p>“Users no longer want to type keywords and then refine, sort, filter, browse and go through a long set of pages to find what they are looking for,” said Belwadi Srikanth, principal for product management at Google Cloud. “They want the AI to understand them very deeply and do the work for them.”</p> <p>Vivek Pradhan, Bunnings’ general manager of data and AI, told the conference that the retailer recognised the limitations of its first-generation, in-house chatbot, Ask Bunnings AI. While it successfully surfaced Bunnings’ 15-year archive of DIY content, it created a clunky experience that required customers to open multiple browser tabs, was unable to refine recommendations, and lacked the ability to process images.</p> <p>Partnering with Google, Bunnings, which runs over 500 stores across Australia and New Zealand, built and launched Buddy in just over six weeks using Gemini Enterprise for CX. Replacing the existing chatbot on the Bunnings website, Buddy is designed to transform the e-commerce experience from “product search to project search”.</p> <p>Rather than typing in keywords for individual items, a customer can tell Buddy they want to build an outdoor deck, for example. The agentic assistant will then recommend the necessary decking boards, underlying structures, measuring tools and power tools, while linking to Bunnings’ trusted how-to videos.</p> <p>Crucially, the Gemini-powered agent is <a href="https://www.techtarget.com/searchenterpriseai/feature/Explore-real-world-use-cases-for-multimodal-generative-AI">multimodal</a>. Customers can upload a photo of a handwritten shopping list to add items to their cart or upload an image of a broken obscure part, such as a specific furniture cam lock, which Buddy will visually identify and locate in the customer’s nearest Bunnings warehouse.</p> <div class="extra-info"> <div class="extra-info-inner"> <h3 class="splash-heading">Read more about AI in Australia</h3> <ul class="default-list"> <li>Melbourne-based Heidi is building its own AI models and launching wearable hardware to automate documentation and <a href="https://www.computerweekly.com/news/366640992/Aussie-AI-health-tech-Heidi-aims-to-cure-clinical-burnout">reduce the administrative burden on doctors</a>.</li> <li>The Australian government has struck a major&nbsp;<a href="https://www.computerweekly.com/news/366639595/Australia-inks-five-year-deal-with-Microsoft-to-drive-AI-and-cloud-adoption">five-year volume sourcing agreement with Microsoft</a>&nbsp;to speed up adoption of AI and cloud technologies across the public sector.</li> <li>ANZ Bank has started&nbsp;<a href="https://www.computerweekly.com/news/366638802/ANZ-rolls-out-AI-agents-for-business-bankers">rolling out AI agents within its new CRM system</a>&nbsp;to help business bankers recover hours of lost productivity by automating tasks and streamlining workflows.</li> <li>Oracle opens <a href="https://www.computerweekly.com/news/366640566/Oracle-opens-Sydney-customer-excellence-centre-to-boost-AI-adoption">AI customer excellence centre in Sydney</a> to help customers navigate technology challenges and turn AI experimentation into business value.</li> </ul> </div> </div> <p>Bunnings managing director Mike Schneider said the roll-out of the technology was a practical example of the business evolving to meet changing customer behaviours. “Our customers come to Bunnings with projects big and small, and Buddy is designed to help make those projects easier to plan and get started,” he said.</p> <p>“This is about embracing and using AI in a practical, responsible way to complement the advice and service our team provides every day, while giving customers more options that suit how they want to interact with us.”</p> <p>Paul Migliorini, vice-president of Google Cloud Australia and New Zealand, said: “AI is at its most powerful when it’s solving everyday problems, and we’re thrilled to be working alongside an iconic Australian brand like Bunnings to bring that to life.</p> <p>“Using Gemini Enterprise for CX, we’re combining the best of our AI and infrastructure with Bunnings’ deep product expertise to create a true expert helper that meets customers right where they are – whether they type or share an image,” he added.</p> <p>Following its progressive roll-out on the Australian website, Buddy will be launched in New Zealand later this year. Bunnings also plans to consolidate its customer service touchpoints, so that Buddy handles initial support queries.</p> <p>It also intends to integrate customer loyalty data, enabling the shopping assistant to offer hyper-personalised recommendations with customer consent, such as automatically suggesting tools from brands that a customer is already using.</p> <div class="pro-features-wrapper"></div> The Australian hardware chain has gone from digital laggard to e-commerce pioneer, teaming up with Google Cloud to launch a conversational AI assistant that turns simple queries into DIY project plans https://cdn.ttgtmedia.com/visuals/ComputerWeekly/Hero%20Images/DIY-tools-adobe.jpg https://www.computerweekly.com/news/366642113/Bunnings-shows-off-AI-shopping-agent-at-Google-showcase Wed, 22 Apr 2026 21:00:00 GMT <p>Google Cloud has unveiled major updates to its enterprise <a href="https://www.computerweekly.com/resources/Artificial-intelligence-automation-and-robotics">artificial intelligence</a> (AI) stack, staking its future on the agentic enterprise, a workplace where AI agents do more than just answer questions, but autonomously reason, delegate and execute complex business workflows.</p> <p>At its Google Cloud Next 2026 conference in Las Vegas, the tech giant introduced a management hub for AI workloads, alongside its eighth-generation tensor processing units (TPUs) and security integrations with Wiz, the cloud-native application protection platform <a href="https://www.computerweekly.com/news/366621040/Largest-ever-cyber-deal-reflects-Googles-CNAPP-ambitions">Google had acquired for $32bn</a>.</p> <p>The announcements come amid the growing proliferation of AI agents that has created a new set of infrastructure, data and security challenges that traditional cloud architectures struggle to support.</p> <p>“The conversation has gone from, ‘Can we build an agent?’ to ‘How do we manage thousands of them?’” said Sundar Pichai, CEO of Google.</p> <p>“That’s why we’re introducing our new Gemini Enterprise Agent Platform. It provides the secure, full-stack connective tissue you need to build, scale, govern and optimise your agents with confidence – a mission control for the agentic enterprise.”</p> <section class="section main-article-chapter" data-menu-title="Taming agent sprawl with central governance"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Taming agent sprawl with central governance</h2> <p>For enterprise IT teams, the <a href="https://www.computerweekly.com/news/366627053/Enterprise-AI-adoption-moving-beyond-experimentation">rapid pace of AI adoption</a> has threatened to create a <a href="https://www.computerweekly.com/news/366640722/Why-AI-agents-are-one-prompt-away-from-ransomware">shadow IT crisis of ungoverned bots</a> and fragmented data silos. Google’s answer is the Gemini Enterprise Agent Platform, which provides a unified framework for developers to build, test&nbsp;and safely deploy agents that can execute multi-step workflows.</p> <p>The platform includes an Agent Registry for indexing internal tools, and an Agent Gateway that acts as “air traffic control”, providing centralised, real-time policy enforcement and ensuring compliance. To handle complex business logic, the platform supports <a href="https://www.techtarget.com/searchcustomerexperience/news/366636690/Agentic-orchestration-the-next-AI-issue-for-CIOs-to-tackle">agentic orchestration</a>, allowing specialised agents to delegate tasks to one another deterministically.</p> <p>Google is also heavily leaning into open standards, incorporating the <a href="https://www.techtarget.com/searchenterpriseai/tip/How-the-Model-Context-Protocol-simplifies-AI-development">model context protocol</a> (MCP) to allow agents to seamlessly interact with Google Cloud services and third-party software-as-a-service (SaaS) applications.</p> <p>“When we gathered at Next a year ago, we talked about how generative AI was transforming organisations around the world,” said Thomas Kurian, CEO of Google Cloud in a blog post. “Today, that future is in-production – the agentic enterprise is real – and deployed at a scale the world has never before seen.”</p> <p>To alleviate integration headaches for CIOs, Kurian noted that instead of piecing together a collection of fragmented systems, Google offers a “vertically optimised stack where everything is co-developed”.</p> <p>Across the Asia-Pacific region, early adopters are already putting agentic workflows into production.</p> <p>For example, Singapore supermarket chain FairPrice Group has <a href="https://www.computerweekly.com/news/366625453/FairPrice-taps-Google-Cloud-for-AI-powered-store">integrated Gemini-powered AI agents into its smart carts</a> to elevate the grocery shopping experience, while Australian financial services firm Macquarie Bank is leveraging Gemini Enterprise to reclaim more than 100,000 hours of team members’ time.</p> <p>In Japan, gaming giants Square Enix and Capcom are using the Gemini Enterprise Agent Platform to build real-time in-game companions and playtesting agents.</p> </section> <section class="section main-article-chapter" data-menu-title="Silicon optimised for training and inference"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Silicon optimised for training and inference</h2> <p>To support the massive compute requirements of continuously running, autonomous agents, Google expanded its AI Hypercomputer infrastructure with its eighth-generation TPUs, splitting the hardware into two purpose-built chips, TPU 8t for training, and TPU 8i for inferencing.</p> <div class="pro-features-wrapper"></div> <p>Designed for scale, TPU 8t uses breakthrough inter-chip interconnect (ICI) technology to network up to 9,600 TPUs and two petabytes of shared high-bandwidth memory in a single superpod. Google claims it delivers three times the processing power of the previous Ironwood generation.</p> <p>TPU 8i is built specifically for the low-latency requirements of agentic reasoning, featuring three times more on-chip SRAM to host larger key-value (KV) caches entirely on-silicon. It also uses a new topology to directly connect 1,152 TPUs in a single pod, delivering an 80% improvement in performance per dollar for inference workloads.</p> <p>Google Cloud also announced it will be among the first providers to offer instances based on the <a href="https://www.computerweekly.com/news/366636948/Nvidia-unveils-Vera-Rubin-architecture-to-power-AI-agents">Nvidia Vera Rubin NVL72 systems</a>, alongside its newly launched Axion Arm-based central processing units.</p> </section> <section class="section main-article-chapter" data-menu-title="Agentic SecOps and cross-cloud data"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Agentic SecOps and cross-cloud data</h2> <p>Recognising that AI agents are only as effective as the data they access, Google Cloud introduced the Agentic Data Cloud, which includes the new Cross-Cloud Lakehouse based on the open-source <a href="https://www.techtarget.com/searchdatamanagement/opinion/Why-Apache-Iceberg-is-essential-for-modern-data-lakehouses">Apache Iceberg table format</a> for analytics datasets. The lakehouse allows organisations to run AI queries on data residing in Amazon Web Services – and soon, Microsoft Azure – without the cost and friction of data egress or supplier lock-in.</p> <p>“You can keep your analytic calculations in one cloud, but connected to data on other clouds, and be able to do so without copying any data from the other clouds,” Kurian noted during a media briefing. “Zero copy for analysis purposes.”</p> <p>Security, naturally, is a concern as agents are granted access to sensitive corporate data and systems of record. To secure agentic workflows, Google announced Agentic Defense that merges Google’s SecOps and threat intelligence capabilities with Wiz’s cloud and AI security platform.</p> <p>The integration includes <a href="https://www.wiz.io/blog/introducing-wiz-ai-app">Wiz’s new AI application protection platform</a>, which provides runtime protection for AI workloads. Security teams can leverage specialised Wiz AI agents, including Red Agents to validate exploitable risks, Blue Agents for threat investigations, and Green Agents to automatically generate code-level remediations for vulnerabilities.</p> <p>Google is already operating at this new agentic scale internally. According to Pichai, the company uses security agents to automatically triage tens of thousands of unstructured threat reports each month, reducing threat mitigation time by more than 90%.</p> <p>In addition, 75% of all new code at Google is now AI-generated and approved by engineers, up from 50% last fall, driven by fully autonomous digital task forces orchestrating code migrations at unprecedented speeds, he noted.</p> <div class="extra-info"> <div class="extra-info-inner"> <h3 class="splash-heading">Read more about AI in APAC</h3> <ul class="default-list"> <li>Agoda, a digital travel platform, has set its sights on&nbsp;<a href="https://www.computerweekly.com/news/366640804/Agoda-scales-AI-strategy-opens-new-APAC-tech-hub">becoming an AI-powered travel companion</a>&nbsp;as it changes how it builds software and moves its tech workforce into a new facility in Bangkok.</li> <li>Singtel and Nvidia have teamed up on a multimillion-dollar facility to&nbsp;<a href="https://www.computerweekly.com/news/366639492/Singtel-Nvidia-to-help-scale-enterprise-AI-deployments">help organisations scale enterprise AI deployments</a>, tackle extreme datacentre power densities, and prepare for the era of embodied AI.</li> <li>Malaysia’s&nbsp;<a href="https://www.computerweekly.com/news/366634082/Ryt-Bank-taps-agentic-AI-for-conversational-banking">Ryt Bank is using its own LLM and agentic AI framework</a>&nbsp;to allow customers to perform banking transactions in natural language, replacing traditional menus and buttons.</li> <li>The Australian government has struck a <a href="https://www.computerweekly.com/news/366639595/Australia-inks-five-year-deal-with-Microsoft-to-drive-AI-and-cloud-adoption">five-year volume sourcing agreement with Microsoft</a> to speed up adoption of AI and cloud technologies across the public sector.</li> </ul> </div> </div> </section> With more AI agents moving to production, Google Cloud is targeting governance, multi-cloud data architecture and purpose-built silicon to help enterprises orchestrate agentic workflows https://cdn.ttgtmedia.com/visuals/ComputerWeekly/HeroImages/using-AI-agent-chatbot-Looker-Studio-adobe.jpg https://www.computerweekly.com/news/366641999/Google-launches-Gemini-Agent-Platform-eighth-generation-TPUs Wed, 22 Apr 2026 08:00:00 GMT <p>Singapore is proposing a global standard to standardise testing methodologies for generative AI and ensure <a href="https://www.computerweekly.com/resources/Artificial-intelligence-automation-and-robotics">artificial intelligence</a> (AI) systems are deployed safely and reliably.</p> <p>The proposed standard, ISO/IEC 42119-8, is the first international standard of its kind. It was announced as Singapore hosts a global AI standardisation plenary meeting this week.</p> <p>Co-organised by the Infocomm Media Development Authority (IMDA) and Enterprise Singapore (EnterpriseSG), the biannual meeting, held in ASEAN for the first time, brings together over 250 AI experts and more than 35 national bodies, including representatives from the US, UK, China, Japan, Germany, France and South Korea.</p> <p>Delivering the opening address on 20 April, IMDA chief executive Ng Cher Pong stressed the urgent need for standardisation, noting that the breakneck pace of AI development has seen the technology evolve from generative AI, to <a href="https://www.techtarget.com/searchenterpriseai/definition/multimodal-AI">multimodal AI</a>, which can process and generate multiple types of data, and now to <a href="https://www.computerweekly.com/feature/Getting-started-with-agentic-AI">agentic AI</a>, all in just over three years. “For AI, the standards-setting process cannot afford to move at a glacial pace,” he said. “Otherwise, it risks being made irrelevant by the speed of change in AI.”</p> <p>Ng described standards as the “quiet infrastructure that enables interoperability, consistency and trust at scale”, helping to drive the adoption and diffusion of new technologies across national borders.</p> <p>Singapore’s proposed standard focuses heavily on benchmarking and <a href="https://www.computerweekly.com/opinion/How-does-red-teaming-test-the-ultimate-limits-of-cyber-security">red teaming</a>, the practice of rigorously testing AI systems for flaws and vulnerabilities. By establishing an important framework for standardised testing approaches, the initiative aims to make AI testing results more reproducible and comparable, ultimately building trust between deployers and users.</p> <p>The framework builds on Singapore’s previous efforts to foster <a href="https://www.computerweekly.com/opinion/The-human-exception-in-AI-governance-Are-we-serious-or-just-ticking-boxes">AI governance</a>, such as the AI Verify Toolkit and the Global AI Assurance Sandbox launched last year.</p> <div class="extra-info"> <div class="extra-info-inner"> <h3 class="splash-heading">Read more about AI in ASEAN</h3> <ul class="default-list"> <li>Agoda, a digital travel platform, has set its sights on&nbsp;<a href="https://www.computerweekly.com/news/366640804/Agoda-scales-AI-strategy-opens-new-APAC-tech-hub">becoming an AI-powered travel companion</a>&nbsp;as it changes how it builds software and moves its tech workforce into a new facility in Bangkok.</li> <li>Singtel and Nvidia have teamed up on a multimillion-dollar facility to&nbsp;<a href="https://www.computerweekly.com/news/366639492/Singtel-Nvidia-to-help-scale-enterprise-AI-deployments">help organisations scale enterprise AI deployments</a>, tackle extreme datacentre power densities, and prepare for the era of embodied AI.</li> <li>Malaysia’s&nbsp;<a href="https://www.computerweekly.com/news/366634082/Ryt-Bank-taps-agentic-AI-for-conversational-banking">Ryt Bank is using its own LLM and agentic AI framework</a>&nbsp;to allow customers to perform banking transactions in natural language, replacing traditional menus and buttons.</li> <li>Google Cloud has officially&nbsp;<a href="https://www.computerweekly.com/news/366637529/Google-Cloud-opens-Bangkok-region-to-support-Thailands-AI-economy">launched its first cloud region in Thailand</a>, fulfilling the company’s&nbsp;<a href="https://www.computerweekly.com/news/366612452/Google-invests-1bn-in-Thailands-cloud-future">pledge to invest $1bn</a>&nbsp;in building its cloud and datacentre infrastructure in the country.</li> </ul> </div> </div> <p>During his speech, Ng also noted how local companies are proactively embracing AI governance, with Changi Airport Group being the first enterprise in Singapore to obtain the ISO/IEC 42001 certification for AI management systems.</p> <p>The certification, launched globally in December 2023, has helped CAG “institutionalise clearer internal accountability, risk assessment and oversight of AI use cases across the organisation”, said Ng.</p> <p>Beyond keeping pace with technological advancements, Ng said global AI standards must cater to diverse regions.</p> <p>“We need to recognise that standards have to be representative and inclusive – not just across sectors and use cases, but also across languages and cultures,” he noted, adding that highly diverse regions like Southeast Asia must be plugged into the standards development process.</p> <p>To bridge this gap, Singapore recently partnered with the American National Standards Institute to conduct a capacity-building workshop on international AI standards for ASEAN member states, equipping them to develop action plans for their jurisdictions.</p> <p>Besides the plenary, IMDA and EnterpriseSG are also hosting a series of events, including the AI Assurance Exchange, which gathers global policymakers and industry leaders to discuss translating AI standards into real-world practice.</p> <p>The efforts are part of Singapore’s broader commitment to develop a trusted AI ecosystem, which includes its national AI Safety Institute and its leadership role in the ASEAN Working Group on AI governance.</p> <div class="pro-features-wrapper"></div> The proposed standard aims to ensure trustworthy AI by standardising benchmarking and red teaming methodologies, as IMDA’s chief urges faster action on global rules https://cdn.ttgtmedia.com/visuals/ComputerWeekly/Hero%20Images/software-testing-1-fotolia.jpg https://www.computerweekly.com/news/366641943/Singapore-pushes-for-global-standard-to-test-generative-AI Mon, 20 Apr 2026 17:44:00 GMT <p>Over 1,000 previously unmapped coral reefs have been discovered stretching across northern Australia, with scientists identifying the massive marine habitats without leaving the office.</p> <p>Led by the Australian Institute of Marine Science (Aims) in partnership with the University of Queensland, the Marine and Coastal Hub project has mapped a vast stretch of underwater ecosystems from Western Australia’s Houtman Abrolhos through to western Cape York in Queensland.</p> <p>Hidden beneath sediment-rich waters, the reefs have largely been invisible to conventional surveys and historically overlooked in conservation and coastal development planning. Previously, the best mapping of the northern coastline was found on maritime charts that failed to distinguish between coral and rocky reefs, as they were designed simply to warn vessels to stay clear of hazards.</p> <p>Aims <a href="https://catalogue.eatlas.org.au/geonetwork/srv/eng/catalog.search#/home">eAtlas</a> project manager Eric Lawrey said the breakthrough was 12 years in the making, sparked by the rise of satellite imagery such as Google Earth. eAtlas is a website and mapping system that contains research, maps and data for tropical Australia.</p> <p>While most people were zooming in on their own homes, Lawrey was scanning the northern Australian coastline, noticing what appeared to be coral reefs and wondering why they were absent from official maps. The challenge, he noted, was that even on a clear day, the reefs were obscured by the region’s highly turbid water.</p> <p>“If you look at any one satellite image, the water just looks like turquoise paint and you can’t really see reefs,” said Lawrey.</p> <p>“But if we overlay 200 images of the area, taken at different times, to create a composite image, all the swirly patterns of the moving water move around and average out while the reefs are constant,” he added. “Their signal gets reinforced and they become much clearer. It allows us to peek deeper into the water column than we could in one image.”</p> <div class="extra-info"> <div class="extra-info-inner"> <h3 class="splash-heading">Read more about IT in ANZ</h3> <ul class="default-list"> <li>Home loan-centric fintech&nbsp;<a href="https://www.computerweekly.com/news/366640336/Lendi-Group-standardises-on-MongoDB-for-AI-ready-data-layer">Lendi Group has standardised on MongoDB</a>&nbsp;as the foundation for an operational data layer designed with AI projects in mind.</li> <li>Western Australia’s Office of the Auditor General has&nbsp;<a href="https://www.computerweekly.com/news/366639954/WA-auditor-flags-weak-Microsoft-365-security-controls-across-state-entities">uncovered weaknesses in M365 configurations</a>&nbsp;across seven government agencies, leading to compromised accounts and data breaches.</li> <li>The Australian government has struck a major&nbsp;<a href="https://www.computerweekly.com/news/366639595/Australia-inks-five-year-deal-with-Microsoft-to-drive-AI-and-cloud-adoption">five-year volume sourcing agreement with Microsoft</a>&nbsp;to speed up adoption of AI and cloud technologies across the public sector.</li> <li>ANZ claims to be the&nbsp;<a href="https://www.computerweekly.com/news/366638802/ANZ-rolls-out-AI-agents-for-business-bankers">first in APAC to deploy Salesforce Agentforce at scale</a>, following a national roll-out of a CRM platform that consolidates data from different systems to ease administrative toil.</li> </ul> </div> </div> <p>The digital expedition required 700 hours of painstaking work to digitise and classify the reefs. The effort has resulted in the first comprehensive view of coral reef boundaries across northern Australia, successfully mapping more than 3,600 coral reefs and 2,900 rocky reefs.</p> <p>Lawrey noted the region harbours a similar quantity of reefs to the Great Barrier Reef, albeit much smaller in individual size.</p> <p>“It’s a vast set of reefs that’s been largely unknown about,” he said. “Well, maybe I should say unmapped, because I’m sure people that are there, or locals, know about all these places.”</p> <p>Funded by the Australian government under the National Environmental Science Program, the project’s success was almost a victim of its own ambition. “The number of reefs we found inshore was a surprise,” said Lawrey. “It became a bit of a problem for our project because we had to map so many of them.”</p> <p>The final datasets have been made openly available through public data portals, such as eAtlas. By revealing what lies beneath the northern coastal waters, the project is expected to pave the way for stronger environmental protection of marine ecosystems that have spent decades hidden in plain sight.</p> <p>Aims has been at the forefront of leveraging technology to monitor and protect Australia’s marine ecosystems. In 2021, it <a href="https://www.computerweekly.com/news/252496333/How-computer-vision-can-protect-coral-reefs">teamed up with Accenture to monitor the health of coral reefs</a> using&nbsp;<a href="https://www.techtarget.com/searchenterpriseai/definition/machine-vision-computer-vision">computer vision</a>.</p> <p>Using a database of underwater imagery, the technology has automated the analysis of coral ecosystems, allowing researchers to track reef health and understand how specific coral species respond to stressful scenarios, such as devastating coral bleaching events.</p> <div class="pro-features-wrapper"></div> Researchers have mapped a previously uncharted network of coral and rocky reefs hidden in the murky coastal waters of Australia’s north, without ever setting foot on a boat https://cdn.ttgtmedia.com/visuals/ComputerWeekly/HeroImages/sea-ocean-wave-surf-Longjourneys-adobe.jpg https://www.computerweekly.com/news/366641744/Scientists-map-coral-reefs-off-northern-Australia Mon, 20 Apr 2026 04:45:00 GMT <p><a href="https://www.computerweekly.com/resources/Artificial-intelligence-automation-and-robotics">Artificial intelligence (AI)</a> is transforming how organisations operate, innovate and compete. Yet, as AI adoption accelerates, so do the demands on energy, water and hardware required to power infrastructure, process data and deploy models and applications at scale.</p> <p>These growing resource needs are creating new challenges for cost optimisation, as well as environmental sustainability and operational resilience, especially as global concerns about resource scarcity intensify.</p> <p>In today’s environment where technology-driven expenses are putting pressure on margins, organisations can no longer afford to treat AI efficiency as an afterthought.</p> <p>AI efficiency is the strategic optimisation of cost, performance and resource use across the AI technology stack to maximise business value. It drives financial results, resilience and sustainability, while reducing waste and risk. Business outcomes, not technical metrics, are the true measure of AI efficiency.</p> <p>Gartner research shows that at least 50% of <a href="https://www.computerweekly.com/news/366612652/APAC-organisations-embrace-generative-AI">generative AI</a> projects will overrun their budgeted costs by 2028 due to poor architectural choices and&nbsp;lack of&nbsp;operational know-how.</p> <p>This trend signals a fundamental shift forcing organisations to move beyond adopting the latest technologies for their own sake. The days of chasing marginal performance gains at any cost are over.</p> <p>The future of AI belongs to those that deploy smarter solutions, not just bigger large language models (LLMs). Organisations need to pivot from scale-at-any-price to efficiency-first strategies if they want sustainable growth, protected margins and long-term leadership as AI adoption increases.&nbsp;</p> <section class="section main-article-chapter" data-menu-title="Hidden costs of inefficient AI practices"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Hidden costs of inefficient AI practices</h2> <p>The rush to adopt AI regardless of strategic fit can often lead to costly missteps.</p> <p>Inefficient AI operations drive up expenses and reduce operational resilience, ultimately undermining investor confidence. As a result, stakeholders are increasingly focused on managing both the cost and value of AI use cases.</p> <p>Over-engineering AI by building systems that are more complex than necessary or misaligned with business needs, drives excessive resource consumption. This not only increases operational costs but also exacerbates environmental challenges at a time when sustainability is under growing scrutiny from regulators and stakeholders.</p> </section> <section class="section main-article-chapter" data-menu-title="Executing AI efficiency"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Executing AI efficiency</h2> <p>Educate consumers and builders of AI capabilities on the business value of optimising AI efficiency and keep them informed to motivate their active participation in optimisation practices. For example, highlight how streamlined AI operations strengthen operational resilience, enabling organisations to better withstand disruptions such as electricity supply constraints.</p> <div class="pro-features-wrapper"></div> <p>A foundational step towards AI efficiency is disciplined use case prioritisation. Evaluate each opportunity for merit, feasibility and return on investment (ROI) to ensure resources are focused on initiatives most likely to deliver meaningful value and align with organisational capabilities.</p> <p>Once high impact use cases are identified, the next priority is embedding best practices throughout the AI technology stack and operational processes.</p> <p>From the tooling perspective, efficiency can be enhanced by moving beyond LLMs alone and leveraging a combination of different AI techniques. This approach enables greater cost-effectiveness, responsiveness, and robustness in enterprise AI systems.</p> <p>Engineering teams can also optimise apps for AI inference activities, which typically accounts for more energy consumption than training. This can be achieved by using smaller models, inference-optimised hardware, caching intermediate outputs and distributing access points closer to consumption.</p> <p>On the <a href="https://www.gartner.com/en/infrastructure-and-it-operations-leaders/topics/i-and-o-strategy">infrastructure</a> side, AI efficiency goals can be further advanced by partnering with cloud providers that demonstrate verifiable commitments to renewable energy use, high energy and water efficiency standards (such as power or water usage effectiveness) and transparent environmental reporting.</p> <p>Another critical area for advancing AI efficiency is monitoring and operations. Actively managing and optimising AI workloads, resource allocation and operational processes can yield significant cost and sustainability benefits.</p> <p>Scheduling large-scale, energy-intensive processes during off-peak hours allows organisations to take advantage of less expensive, greener energy sources. Carefully distinguishing between workflows that require real-time processing versus those suitable for batch processing can also reduce costs.</p> <p>Additionally, <a href="https://www.computerweekly.com/news/366641816/How-the-AI-boom-is-reshaping-tech-cost-management">adopting GreenOps extends FinOps principles</a> by applying sustainability metrics across IT operations. Continuously tracking energy consumption, greenhouse gas emissions and waste generation helps ensure ongoing optimisation of AI workloads while supporting broader environmental goals.</p> <p>These are just a few ways to embed AI efficiency into an organisation. True impact requires action across the overall AI technology stack, including applications, selecting the right AI techniques and tools, and implementing robust data management practices.</p> </section> <section class="section main-article-chapter" data-menu-title="Measuring success"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Measuring success</h2> <p>AI efficiency metrics should be prioritised based on their impact on business outcomes. These measures reflect how ready a technology stack is to support critical business processes and deliver results.</p> <p>Start by tracking the percentage of stakeholders trained on efficient AI principles. This metric shows how effectively the organisation is building a culture of efficiency, ensuring employees and leaders understand both the business value and practical steps required for optimisation.</p> <p>Next, monitor the proportion of AI workloads running on sustainability-aware and reliable infrastructure. Prioritise deployments powered by verified renewable energy sources, measured against provider sustainability benchmarks.</p> <p>Track data management efficiency by measuring the reduction in total data storage requirements and the volume of data transferred for AI workloads, which indicates improved data handling and lower resource consumption.</p> <p>Finally, measure asset reuse rates across the portfolio. Evaluate how often models or software components are leveraged in multiple projects to minimise duplication of effort and maximise resource use.</p> <p>By moving beyond cost optimisation and embedding efficiency across every layer of AI deployments, organisations can unlock sustainable growth while meeting today’s business challenges.</p> <p><i>Gabriele Rigon is a director-analyst at Gartner, specialising in natural language technologies and contributes to research relating to AI efficiency, GenAI, AI agents and AI governance.</i></p> </section> With half of generative AI projects expected to overrun budgets by 2028, IT leaders must drive efficiency across the AI stack to protect margins and address environmental challenges https://cdn.ttgtmedia.com/visuals/ComputerWeekly/Hero%20Images/Future-tech-hero-AdobeStock_362585382.jpg https://www.computerweekly.com/opinion/How-to-improve-AI-efficiency-beyond-cost-optimisation Fri, 17 Apr 2026 01:42:00 GMT <p>For years, companies have been adopting <a href="https://www.techtarget.com/searchcloudcomputing/feature/3-FinOps-trends-to-look-out-for-in-2026">financial operations (FinOps)</a> practices to manage and optimise their cloud computing expenses. However, the growing adoption of generative artificial intelligence (GenAI) is rewriting the rules of technology budgeting.</p> <p>According to the FinOps Foundation’s <a href="https://data.finops.org/"><i>2026 State of FinOps</i></a> report, an overwhelming 98% of global FinOps practitioners are now tasked with managing AI spend, an increase from just 31% in 2024. Furthermore, AI cost management has become the single most sought-after skill set for technology finance teams this year.</p> <p>“It’s still fairly early days with AI adoption. Most organisations are in the proof-of-concept phase, figuring things out,” said Matt Pinter, Asia-Pacific field chief technology officer at Apptio, an IBM company specialising in software for technology cost management.</p> <p>AI pricing can vary based on the types of services and deployment models. For off-the-shelf tools such as ChatGPT or Google’s Gemini, the primary billing metric is the token, a fundamental unit of data processed by the AI.</p> <p>“That seems to be what the industry has standardised on. Tokens are the main billing mechanism,” Pinter said. As a result, optimising queries to reduce token usage is becoming one of the most effective ways to control AI costs.</p> <p>Against this backdrop, companies are beginning to treat tokens like a corporate currency. Some organisations are exploring <a href="https://www.computerweekly.com/news/366641232/Digital-Realty-CTO-on-AI-tokenomics-and-datacentre-infrastructure">tokenomics</a>, giving developers a monthly allowance of tokens for coding and code reviews.</p> <p>“You give somebody a budget of tokens and say, ‘Here’s what you have to do your job.’ They then figure out how to get their work done within the allocated budget,” Pinter said. “You can see that mindset shift starting to happen, where engineers are saying, ‘I want to make sure I’m using it responsibly.’”</p> <p>The focus on developers reflects the growing trend of <a href="https://www.computerweekly.com/blog/Open-Source-Insider/FinOps-Foundation-on-state-of-the-FinOps-nation-AI-value-skills-at-the-fore">shifting left in FinOps</a>, where costs are optimised through mechanisms such as <a href="https://www.techtarget.com/searchcloudcomputing/feature/Save-money-on-instances-with-these-cloud-discounts">committed usage discounts</a> and right-sized instances earlier in the <a href="https://www.techtarget.com/searchsoftwarequality/definition/software-development-life-cycle-SDLC">software development lifecycle</a> before a workload reaches production.</p> <p>According to the FinOps Foundation, FinOps teams have also started to engage with platform engineering and enterprise architecture teams, building pricing calculators and offering pre-deployment guidance.</p> <section class="section main-article-chapter" data-menu-title="The hidden costs of homegrown AI"> <h2 class="section-title"><i class="icon" data-icon="1"></i>The hidden costs of homegrown AI</h2> <p>While off-the-shelf AI services offer convenience, building homegrown AI can be significantly more expensive. It requires securing highly coveted graphics processing units (GPUs) in the datacentre or the cloud, and addressing what Pinter calls “the hidden cost of AI”.</p> <p>“It gets a lot more complex because now you’re talking about the infrastructure to support homegrown AI solutions,” he said. “If they are in the datacentre, then you need to consider the electricity costs to power these systems.”</p> <p>Increasingly, the environmental footprint of AI is <a href="https://www.computerweekly.com/blog/CW-Developer-Network/GreenOps-Revenium-To-optimise-AI-for-cost-and-sustainability-start-with-outcomes">tying FinOps to GreenOps</a>, particularly in the Asia-Pacific region where new climate laws mandate companies to measure and reduce carbon emissions. By optimising cloud usage, organisations can simultaneously lower their bills and carbon footprints.</p> <p>Beyond public cloud services, nearly half of FinOps teams are actively managing physical datacentre costs to capture the full footprint of AI computing demands, according to the FinOps Foundation report. These teams are also working with <a href="https://www.techtarget.com/whatis/definition/environmental-social-and-governance-ESG">environmental, social and governance (ESG)</a> teams on sustainability initiatives.</p> </section> <section class="section main-article-chapter" data-menu-title="The search for ROI"> <h2 class="section-title"><i class="icon" data-icon="1"></i>The search for ROI</h2> <p>Despite significant investments in AI, many companies struggle to articulate its return on investment (ROI). “Many customers are missing that right now,” Pinter said. “They’ve been told, ‘Go do AI’, but they don’t have a clear end state in mind.”</p> <div class="pro-features-wrapper"></div> <p>With <a href="https://www.ciodive.com/news/ai-spend-management-cios-finops/817620/">just 7.5% of enterprises baking FinOps into AI projects</a>, according to IDC, practitioners are encouraging more businesses to calculate the exact unit economics of AI. For example, a bank that processes home loans could establish a baseline cost, say, $8 per loan for 1,000 loans a month, and measure the financial impact of AI implementation.</p> <p>“Ideally with AI, you should see the number of mortgages increase and the processing time decrease,” Pinter said. “You could say, ‘We’ve tripled that and lowered our unit cost by 10%.’”</p> <p>This is where the <a href="https://www.tbmcouncil.org/learn-tbm/what-is-tbm/">Technology Business Management (TBM) model</a> can help. Pinter noted that the latest version of model provides a way for enterprises to work out the cost structure of different AI services and deployment models, bringing together traditional IT financial management (ITFM) and FinOps.</p> <p>“It’s about being able to look at multiple different disciplines and provide that single pane of glass, where you can get into chargeback and look at SaaS and on-premise applications,” he said. “It’s bringing all that together and providing a vehicle to effectively charge back all the costs that the IT organisation is incurring.”</p> <p>Ironically, the solution to managing AI costs involves more AI. Pinter expects AI-driven anomaly detection to become essential for preventing bill shocks from misconfigured cloud instances. Natural language chatbots could also replace <a href="https://www.computerweekly.com/feature/How-AI-is-shaping-the-future-of-business-intelligence">business intelligence dashboards</a>, allowing executives to query data for instant insights.</p> <p>But technology alone isn’t enough to drive cost-saving FinOps practices. The single biggest barrier to adopting FinOps, whether in mature cloud markets such as Australia or technology hubs like Taiwan and Singapore, is human resistance.</p> <p>“It’s the culture shift to get everybody bought into it,” he said. “You might not have executives fully on board, and engineers might be apprehensive. Getting organisational buy-in, where everyone says, ‘Yes, this is what we’re going to do’, is the biggest challenge.”</p> <div class="extra-info"> <div class="extra-info-inner"> <h3 class="splash-heading">Read more about FinOps</h3> <ul class="default-list"> <li>Nearly six in 10 enterprises have built <a href="https://www.techtarget.com/searchcloudcomputing/tip/The-business-case-for-FinOps-to-control-cloud-spending">FinOps teams to advise on, manage or execute cloud cost optimisation</a> strategies. So, the question is, what are you waiting for?</li> <li>FinOps teams are <a href="https://www.ciodive.com/news/ai-spend-management-cios-finops/817620/">tackling the difficult nature of AI spend</a> to help tech chiefs get costs under control, analysts said during Flexera’s FinOps Forward 2026 event.</li> <li><a href="https://www.techtarget.com/searchcloudcomputing/tip/What-are-FinOps-tools-and-how-do-I-choose-one">FinOps tools</a> help organisations optimise cloud spending and use. Review the different native and third-party options to find the best fit for your needs.</li> <li>Gamification can turn the <a href="https://www.computerweekly.com/opinion/How-gamification-can-turn-cloud-cost-battles-into-a-team-sport">combative relationship between finance and tech</a> into a team sport that helps improve cloud cost management and financial results.</li> </ul> </div> </div> </section> FinOps practitioners are stepping up to manage AI expenses, optimise token usage and align cost-saving measures with sustainability goals to improve returns from AI investments https://cdn.ttgtmedia.com/visuals/German/article/hidden-costs.jpg https://www.computerweekly.com/news/366641816/How-the-AI-boom-is-reshaping-tech-cost-management Thu, 16 Apr 2026 05:00:00 GMT <p>It looks like we’re heading for a new <a href="https://en.wikipedia.org/wiki/American_Century">American Century</a> when it comes to datacentre development, with US capacity set to triple to a staggering 102GW if all projected capacity in the pipeline comes to fruition.&nbsp;</p> <p>Meanwhile, the UK – with about 1.7GW currently – will reach about 4GW, and looks set to slip in the rankings in terms of absolute <a href="https://www.computerweekly.com/resources/Data-centre-capacity-planning">datacentre capacity</a>&nbsp;and in terms of <a href="#MW-GDP">megawatts (MW) to gross domestic product (GDP)</a>.</p> <p>That’s according to figures from commercial property agent Cushman &amp; Wakefield, plus GDP data from the International Monetary Fund (IMF), with analysis by Computer Weekly.</p> <figure class="main-article-image full-col" data-img-fullsize="https://www.computerweekly.com/rms/computerweekly/bigNumbersCapGrowth-15Apr-f.jpg"> <img data-src="https://www.computerweekly.com/rms/computerweekly/bigNumbersCapGrowth-15Apr-f_mobile.jpg" class="lazy" data-srcset="https://www.computerweekly.com/rms/computerweekly/bigNumbersCapGrowth-15Apr-f_mobile.jpg 960w,https://www.computerweekly.com/rms/computerweekly/bigNumbersCapGrowth-15Apr-f.jpg 1280w" alt="Graphic shows UK ranks 10th in datacentre capacity growth" height="131" width="559"> <div class="main-article-image-enlarge"> <i class="icon" data-icon="w"></i> </div> </figure> <p><a href="https://www.computerweekly.com/news/366641660/Go-West-US-datacentres-head-for-available-and-cheap-energy">Also in the US</a>, Virginia is set to retain its nickname of “datacentre alley”, with capacity in the pipeline that will see it retain its number one region ranking and take it to more than 10GW. London, however, could move up the rankings here to become the sixth largest datacentre region if all planned capacity is built.</p> <section class="section main-article-chapter" data-menu-title="UK datacentre capacity set to slip"> <h2 class="section-title"><i class="icon" data-icon="1"></i>UK datacentre capacity set to slip&nbsp;</h2> <p>The UK currently ranks fourth in megawatt capacity terms – behind the US, China and Japan – with about 1.76GW of capacity. But it will slip to seventh in terms of total operational and planned capacity, with India, Malaysia and Australia set to leapfrog it.&nbsp;</p> <p>The UK ranks eighth currently in terms of MW to GDP, but will slip to 10th if we measure all current and planned capacity.&nbsp;</p> <figure class="main-article-image full-col" data-img-fullsize="https://www.computerweekly.com/rms/computerweekly/dcCapGrowth-15Apr-f.jpg"> <img data-src="https://www.computerweekly.com/rms/computerweekly/dcCapGrowth-15Apr-f_mobile.jpg" class="lazy" data-srcset="https://www.computerweekly.com/rms/computerweekly/dcCapGrowth-15Apr-f_mobile.jpg 960w,https://www.computerweekly.com/rms/computerweekly/dcCapGrowth-15Apr-f.jpg 1280w" alt="Graphic shows datacentre capacity growth by country" height="388" width="559"> <div class="main-article-image-enlarge"> <i class="icon" data-icon="w"></i> </div> </figure> <p>In terms of datacentre regional capacity, London ranks eighth with 1.53GW. It stays at eighth if projects under construction are taken into account (rising to 1.82GW), but jumps to sixth if the total pipeline is considered (3.25GW), although that may include projects that have not gained planning consent and may never do so.&nbsp;</p> <p>It’s possible that “London” takes into account much more than that region in Cushman &amp; Wakefield’s figures, however. <a href="https://www.computerweekly.com/news/366640935/Data-dive-Government-2030-datacentre-capacity-targets-look-shaky">Computer Weekly research</a> (<a href="#pipeline-numbers"><em>see box: Nailing down datacentre pipeline numbers</em></a>) into installed datacentre capacity has the whole of the UK at about 1.6GW, including <a href="https://www.computerweekly.com/news/366640447/Hit-the-north-UK-datacentre-focus-shifts-to-M62-and-points-north">the M62 region plus the North East and Scotland</a>.&nbsp;</p> <figure class="main-article-image half-col" data-img-fullsize="https://www.computerweekly.com/rms/computerweekly/top10regions-15Apr-h.jpg"> <img data-src="https://www.computerweekly.com/rms/computerweekly/top10regions-15Apr-h_half_column_mobile.jpg" class="lazy" data-srcset="https://www.computerweekly.com/rms/computerweekly/top10regions-15Apr-h_half_column_mobile.jpg 960w,https://www.computerweekly.com/rms/computerweekly/top10regions-15Apr-h.jpg 1280w" alt="Table shows top 10 regions for datacentre capacity" height="361" width="279"> <div class="main-article-image-enlarge"> <i class="icon" data-icon="w"></i> </div> </figure> <figure class="main-article-image half-col" data-img-fullsize="https://www.computerweekly.com/rms/computerweekly/dcGrowthTable-15Apr-h.jpg"> <img data-src="https://www.computerweekly.com/rms/computerweekly/dcGrowthTable-15Apr-h_half_column_mobile.jpg" class="lazy" data-srcset="https://www.computerweekly.com/rms/computerweekly/dcGrowthTable-15Apr-h_half_column_mobile.jpg 960w,https://www.computerweekly.com/rms/computerweekly/dcGrowthTable-15Apr-h.jpg 1280w" alt="Table shows global datacentre capacity rankings" height="456" width="279"> <div class="main-article-image-enlarge"> <i class="icon" data-icon="w"></i> </div> </figure> <p>Ireland currently lies 10th in terms of installed capacity, with 1.27GW. It slides to 13th in terms of total under construction and pipeline, at around 2GW. But in terms of MW to GDP, it sits second, only dropping to third when we measure currently installed and all pipeline against the projected 2030 GDP.</p> </section> <section class="section main-article-chapter" data-menu-title="Indonesia and Malaysia set for huge relative growth"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Indonesia and Malaysia set for huge relative growth</h2> <p>While the US looks determined to maintain its position in the world datacentre rankings – it has a projected capacity growth rate of 221% – it is outstripped in growth terms by some countries that look keen to expand datacentre capacity.</p> <div class="pro-features-wrapper"></div> <p>The shooting star among these is Indonesia, with projected growth of 451% in capacity terms (to 2.1GW). Behind it is Malaysia at 279% projected growth (to 4.87GW).</p> <p>They appear to be aiming at becoming providers of datacentre capacity for regional economies such as Singapore, Thailand and Vietnam.&nbsp;</p> <p>Singapore had been the dominant regional hub, but power and land constraints saw it call a halt to further datacentre development. This has been somewhat reversed, but Indonesia and Malaysia have seen an opportunity to make use of their resources, with Amazon, Google, Microsoft and Meta pledging billions of dollars towards datacentre projects there.&nbsp;</p> </section> <section class="section main-article-chapter" data-menu-title="Data sovereignty a big factor for some"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Data sovereignty a big factor for some</h2> <p>Meanwhile, the Cushman &amp; Wakefield numbers show growth in datacentre capacity of 200% or more for Australia, India and Brazil.&nbsp;</p> <p>Australia benefits from vast amounts of land and renewable energy, allied with some of the world’s strictest data sovereignty laws. The latter has forced huge local builds that wouldn’t exist if the data could be hosted in cheaper regional hubs. It is set for datacentre capacity growth of 224% (to 4.8GW) and MW to GDP growth of 149%.</p> <p>India’s sizeable growth – 222% in capacity (to 5.1GW) and 90% growth in MW to GDP – is driven by regulatory mandates, a gargantuan domestic user base and structural cost advantages. India has implemented some of the world’s most stringent data residency requirements. Also, global companies that previously served India from hubs in Singapore or Dubai are now legally required to build or lease physical capacity inside India.</p> <p>Brazil benefits from being a key economic centre for South America, is a primary landing point for subsea cables on the continent, has lots of renewable energy and – this is becoming a theme – has strict data sovereignty requirements. It has a projected capacity growth rate of 218% (to 1.6GW) with a MW to GDP growth of 147%.</p> <p>Here, similarly to India, Brazilian law encourages companies to store the data of Brazilian citizens on-shore, which has forced cloud providers to expand local regions in São Paulo and Rio de Janeiro.</p> <p>In Europe, meanwhile, the UK, France and Germany are hitting structural limits in terms of power supply, with waits measured in years to get a grid connection. At the same time, there is a scarcity of land and strict sustainability requirements.</p> <p>Having said that, these are mature markets, and where there are constraints in terms of new construction in established centres, that is now moving towards other areas in nearby countries such as Italy, Spain and Poland, or within countries, such as the shift north in the UK.</p> <div class="extra-info"> <div class="extra-info-inner"> <h3 class="splash-heading">Read more about datacentre development</h3> <ul class="default-list"> <li><a href="https://www.computerweekly.com/news/366640935/Data-dive-Government-2030-datacentre-capacity-targets-look-shaky">Data dive: UK government’s 2030 datacentre capacity targets look shaky</a>: We look at UK datacentre capacity – current and projected – and find DSIT’s 2030 target for 6GW of AI-capable capacity is currently out of reach, unless operators get a move on.</li> <li><a href="https://www.computerweekly.com/news/366640447/Hit-the-north-UK-datacentre-focus-shifts-to-M62-and-points-north">Hit the north! UK datacentre focus shifts to M62 and points north</a>: Barbour ABI data shows an 8GW total datacentre pipeline, with most big projects in the north and Scotland, while London and the M4 corridor account for about 25% of projected capacity.</li> </ul> </div> </div> <ul class="default-list"></ul> </section> <section class="section main-article-chapter" data-menu-title="Maxed out Paddy"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Maxed out Paddy</h2> <p>Ireland, specifically Dublin, built out its capacity years before the rest of Europe, but was the first major global hub to hit a “grid ceiling”. Current capacity is 1.2GW. Since 2021, state-owned grid operator EirGrid has implemented a functional moratorium on new datacentre connections in the greater Dublin area. By 2024, datacentres consumed 21% of Ireland’s total electricity – more than all its homes combined.</p> <p>Now, under new regulations, if a company wants to build a new datacentre of more than 10MW, they must provide their own on-site generation – like gas turbines or battery arrays – to back up 100% of their demand.&nbsp;</p> <p>Meanwhile, Ireland is the European headquarters for virtually every major US tech firm, and because they book profits in Ireland, GDP is roughly 40% higher than the actual value produced by the Irish population. So, its MW to GDP growth rate in these figures is 5.7%.</p> <p>For that reason, Ireland’s GDP is considered unreliable for measuring actual domestic economic health.</p> </section> <section class="section main-article-chapter" data-menu-title="What does MW to GDP tell us?"> <h2 class="section-title"><i class="icon" data-icon="1"></i><a id="MW-GDP"></a>What does MW to GDP tell us?</h2> <p>If we measure a country’s datacentre capacity in megawatts (MW) against its gross domestic product (GDP), we get some idea of whether that capacity is primarily a utility supporting its own domestic economy or effectively an export designed to process data for the rest of the world.</p> <p>By looking at how that will change, we can also see the trajectory of that country relative to its digital economy.&nbsp;</p> <p>The ratio of MW to GDP is a measure of digital infrastructure compared to the economy more broadly. In the datacentre age, it’s like measuring “miles of track per capita” or “steel production per GDP” as measures of industrial development.</p> <figure class="main-article-image full-col" data-img-fullsize="https://www.computerweekly.com/rms/computerweekly/dcMWgdpGrowth-15Apr-f.jpg"> <img data-src="https://www.computerweekly.com/rms/computerweekly/dcMWgdpGrowth-15Apr-f_mobile.jpg" class="lazy" data-srcset="https://www.computerweekly.com/rms/computerweekly/dcMWgdpGrowth-15Apr-f_mobile.jpg 960w,https://www.computerweekly.com/rms/computerweekly/dcMWgdpGrowth-15Apr-f.jpg 1280w" alt="Graphic shows projected datacentre megawatts to gross domestic product " height="181" width="559"> <div class="main-article-image-enlarge"> <i class="icon" data-icon="w"></i> </div> </figure> <p>We can see from the numbers that differing models emerge.</p> <p>Very high ratios of MW capacity to GDP – for example, Ireland, Indonesia, Malaysia – suggest a country positioned as a “digital exporter”. They consume power domestically to process data for other countries. Their MW capacity is high, while GDP is low.&nbsp;</p> <p>Meanwhile, very low ratios of MW capacity to GDP – for example, Japan, the UK, the Netherlands – will often be mature, service- or manufacturing-heavy economies where datacentres support domestic business rather than act as an export.</p> <p>Most of the world’s developed economies fall into the latter category, while some rapid movers from a less-developed starting point fall into the former.</p> <figure class="main-article-image full-col" data-img-fullsize="https://www.computerweekly.com/rms/computerweekly/bigNumbersMwGDPGrowth-15Apr-f.jpg"> <img data-src="https://www.computerweekly.com/rms/computerweekly/bigNumbersMwGDPGrowth-15Apr-f_mobile.jpg" class="lazy" data-srcset="https://www.computerweekly.com/rms/computerweekly/bigNumbersMwGDPGrowth-15Apr-f_mobile.jpg 960w,https://www.computerweekly.com/rms/computerweekly/bigNumbersMwGDPGrowth-15Apr-f.jpg 1280w" alt="Graphic shows UK ranks 12th in datacentre MW to GDP growth" height="134" width="557"> <div class="main-article-image-enlarge"> <i class="icon" data-icon="w"></i> </div> </figure> <p>Two countries, however, seem set for rapid but balanced growth – the US and Australia. They’re both countries with vast space and scope for renewable energy, and they have developed economies. With projected MW to GDP growth of 150% or more, that could indicate a sweet spot in terms of economic development.&nbsp;</p> <div class="extra-info"> <div class="extra-info-inner"> <h3 class="splash-heading"><a id="pipeline-numbers"></a>Nailing down datacentre pipeline numbers</h3> <p>We must treat a lot of the numbers around datacentre development with some dosage of salt. <a href="https://www.computerweekly.com/news/366640935/Data-dive-Government-2030-datacentre-capacity-targets-look-shaky">Computer Weekly recently ran analyses</a> of installed and pipeline capacity for the UK. In some cases, those figures accord with Cushman &amp; Wakefield’s research.</p> <p>For currently installed UK capacity, Computer Weekly calculated 1.6GW using data gained from Electricity Performance Certificate registers. Cushman &amp; Wakefield posts a total 1.7GW.&nbsp;</p> <p>When it comes to pipeline, Computer Weekly took data from construction tracking analyst Barbour ABI that lists all projects currently in planning, some of which have gained consent, while others have not. Within this data, some megawatt capacity numbers had to be estimated because planning documents don’t mandate recording of proposed datacentre capacity.&nbsp;</p> <p>Computer Weekly calculations for the UK pipeline total around 8GW, with 5.9GW having planning consent or being under construction. Cushman &amp; Wakefield’s equivalent figure is around 2.3MW.</p> <p>If we use the Computer Weekly calculations for pipeline, we get capacity growth in excess of 500%. That seems unlikely, with the Cushman &amp; Wakefield numbers looking more realistic. How does such a disparity occur? The Barbour ABI project listings likely&nbsp;include a fair amount of projects for which planning consent has been sought but will never happen.&nbsp;</p> <p>We’ve also got to take into account that “pipeline” is inherently a little “fuzzy”. Some projects that have consent now won’t be completed for 10 years – the <a href="https://www.computerweekly.com/news/366639995/Enormous-AI-growth-zone-datacentre-gets-planning-approval">1GW Elsham Tech Park in the UK</a>, for example – while some projects won’t even make the current pipeline because they’re going to be shorter in duration and have not yet been announced or had plans submitted.&nbsp;</p> <p>A more accurate measure of pipeline is gained by tracking construction timelines and asking the question about a specific future date for expected completed capacity. That’s possible with UK data from Barbour ABI, for example, but for countries with differing planning regimes and data sources, and developers that tend to keep their cards close to their chests, it is likely to result in a patchy picture.&nbsp;</p> <p>All this shows the difficulty of assessing current and proposed datacentre capacity. And that’s just domestically. Cushman &amp; Wakefield clearly makes use of its international presence to calculate pipeline and installed capacity worldwide. We can be sure there are many ways in which installed datacentre capacity is recorded and many slips twixt intent and reality in terms of pipeline, but at least we get the lay of the land.&nbsp;</p> </div> </div> </section> Looking at datacentre development internationally, we see how the UK faces apparent relative decline, how countries are responding to the AI age, and what MW vs GDP can tell us https://cdn.ttgtmedia.com/visuals/ComputerWeekly/Hero%20Images/US:UK%20flags-Fotolia.jpg https://www.computerweekly.com/feature/Data-dive-A-new-American-Century-in-the-datacentre-pipeline Wed, 15 Apr 2026 08:20:00 GMT <p>Singapore’s OCBC Bank has launched a <a href="https://www.computerweekly.com/news/366612652/APAC-organisations-embrace-generative-AI">generative artificial intelligence</a> (GenAI) training programme for its 900 wealth advisors in Singapore, in a bid to improve sales performance and client engagements.</p> <p>The six-month training programme, which OCBC touted as a first of its kind for a bank in Singapore, uses <a href="https://www.computerweekly.com/feature/LLMs-explained-A-developers-guide-to-getting-started">large language models</a> to simulate realistic customer scenarios. This allows advisors to hone their pitches and advisory skills on their work devices at their own pace, rather than waiting weeks for a supervisor’s availability.</p> <p>Within the first three months of its implementation, wealth advisors who went through the training secured twice as many weekly client appointments as peers who had not yet used the programme. They also recorded a 50% uplift in revenue compared with the three months prior.</p> <p>Previously, skills training was conducted in-person and one-on-one. Because supervisors have to juggle their own duties while coaching up to 10 staff members, wealth advisors could wait up to three weeks just to secure a training session. This traditional method also risked inconsistent evaluation standards and feedback quality across different managers.</p> <p>Developed over 12 months, the programme uses the bank’s anonymised proprietary data on customer behaviour to generate dynamic, lifelike role play scenarios.</p> <p>The AI responds naturally to the advisor, mimicking a real client looking to build a long-term investment portfolio, identify their risk profile, or adjust strategies amid market movements.</p> <p>The system removes the emotional bias of human-led coaching while ensuring that all advisors are consistently trained to meet strict regulatory and professional standards.</p> <section class="section main-article-chapter" data-menu-title="Gap analysis"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Gap analysis</h2> <p>Following each simulated session, supervisors will receive a GenAI gap-analysis report detailing the advisor’s competency levels and highlighting specific areas for improvement. This allows managers to deliver highly targeted, in-person coaching to close those skills gaps.</p> <p>Sunny Quek, OCBC’s head of global consumer financial services, said the programme helps advisors quickly grasp complex product knowledge and financial industry regulations.</p> <p>“In wealth management, these experiences are especially crucial because advisory requires empathy, judgement and trust – qualities that only human advisors can bring,” said Quek. “By marrying AI precision with the human touch, we ensure our advisors are not just well-trained, but future-ready for customers’ growing sophistication in their wealth management needs.”</p> <p>For advisors on the ground, the flexibility of the tool has been a major draw. Ng Zuolin, an OCBC wealth advisor, said the platform has accelerated her learning curve since entering the banking industry.</p> <p>“With the GenAI training programme, I can practice the scenarios on my own, and as many times as possible, to pick up wealth advisory skills more quickly to serve customers better,” she said. “Plus, with the feedback from the GenAI training, my supervisor can identify my weaknesses and help me tackle them faster during our in-person training sessions.”</p> <p>OCBC’s wealth advisors serve a broad spectrum of retail banking customers, ranging from personal banking clients with assets under management (AUM) of under S$350,000 to Private Premier clients with AUM exceeding S$1.5m.</p> <p>The bank plans to roll out the GenAI programme to its markets in Malaysia and Hong Kong at a later stage. The training content, customer scenarios and learning pathways will be localised to reflect specific regulatory requirements, products and customer behaviours in those jurisdictions.</p> <div class="pro-features-wrapper"></div> <div class="extra-info"> <div class="extra-info-inner"> <h3 class="splash-heading">Read more about AI in ASEAN</h3> <ul class="default-list"> <li>Agoda, a digital travel platform, has set its sights on <a href="https://www.computerweekly.com/news/366640804/Agoda-scales-AI-strategy-opens-new-APAC-tech-hub">becoming an AI-powered travel companion</a> as it changes how it builds software and moves its tech workforce into a new facility in Bangkok.</li> <li>Singtel and Nvidia have teamed up on a multimillion-dollar facility to&nbsp;<a href="https://www.computerweekly.com/news/366639492/Singtel-Nvidia-to-help-scale-enterprise-AI-deployments">help organisations scale enterprise AI deployments</a>, tackle extreme datacentre power densities, and prepare for the era of embodied AI.</li> <li>Malaysia’s <a href="https://www.computerweekly.com/news/366634082/Ryt-Bank-taps-agentic-AI-for-conversational-banking">Ryt Bank is using its own LLM and agentic AI framework</a> to allow customers to perform banking transactions in natural language, replacing traditional menus and buttons.</li> <li>Google Cloud has officially <a href="https://www.computerweekly.com/news/366637529/Google-Cloud-opens-Bangkok-region-to-support-Thailands-AI-economy">launched its first cloud region in Thailand</a>, fulfilling the company’s&nbsp;<a href="https://www.computerweekly.com/news/366612452/Google-invests-1bn-in-Thailands-cloud-future">pledge to invest $1bn</a>&nbsp;in building its cloud and datacentre infrastructure in the country.</li> </ul> </div> </div> </section> First programme of its kind allows wealth advisors to hone their pitches through realistic AI role play, resulting in double the client appointments and a 50% growth in revenue in three months https://cdn.ttgtmedia.com/visuals/ComputerWeekly/Hero%20Images/financial-results-chart-graph-2-adobe.jpeg https://www.computerweekly.com/news/366641609/OCBC-rolls-out-generative-AI-training-for-wealth-advisors Wed, 15 Apr 2026 06:45:00 GMT <p>For all the hype surrounding <a href="https://www.computerweekly.com/resources/Artificial-intelligence-automation-and-robotics">artificial intelligence (AI)</a> and its potential to transform the financial sector, one of the world’s largest multinational banks believes that customers will still want to talk to a human.</p> <p>During a recent fireside chat at the Gitex AI Asia 2026 conference in Singapore, Alvaro Garrido, a senior executive at Standard Chartered, outlined how the financial institution is managing the deployment of AI across its global footprint.</p> <p>Rather than view the technology merely as a tool for mass automation and cost-cutting, Garrido, the bank’s chief operating officer for technology and operations and CIO for information security and data, described it as an “injection of support” for the bank’s workforce. To that end, the company has enrolled some 80,000 employees in internal AI training programmes, of which roughly 33,000 have already completed coursework.</p> <p>“We always debated whether it’s a technology-driven journey, an output-driven journey or a cost-reduction journey,” Garrido told Zina Cinker, a condensed matter physicist and exponential technology strategist, who moderated the discussion. “For us, we put the individual at the centre, because people are actually driving the transformation in the bank.”</p> <p>The financial sector has long been perceived as traditional and risk-averse, dealing intimately with people's livelihoods. Yet beneath the surface, Standard Chartered is integrating AI and <a href="https://www.techtarget.com/searchenterpriseai/definition/machine-learning-ML">machine learning</a> deep into its operations. Beyond front-end customer service, the bank is also using the technology to power self-healing infrastructure that detects system anomalies and to combat sophisticated financial crime and fraud.</p> <p>But when it comes to sensitive decisions such as credit assessments, the bank remains cautious. “For every process that we are injecting AI into, we absolutely make sure that all the ethical evaluations for any model [are done] to mitigate bias. We like to believe that there’s always a human in the loop,” Garrido said.</p> <p>Paradoxically, he added, applying the technology rigorously could eventually lead to a “much more objective way to deliver credit” by analysing data points that human loan officers might overlook.</p> <p>Operating in highly regulated markets – from the UK and the United Arab Emirates to China and Singapore – presents a patchwork of regulatory frameworks for any global bank. However, Garrido praised the Monetary Authority of Singapore as one of the most progressive and decisive regulators in the world, noting that the agency’s speed often challenges the bank to innovate faster just to keep up.</p> <p>To manage cross-border deployment complexities, Standard Chartered builds its AI capabilities on a centralised, highly standardised technology foundation, leaving localised customisation to regional teams. The bank has also developed safe ways for teams to train AI models using production data, rather than relying on the synthetic or obfuscated data used in the past.</p> <p>Yet, even with internal safeguards, the rapid adoption of AI brings significant risks. As an executive who also oversees the bank’s cyber security operations, Garrido said his primary concern remains the fragility of the financial and technology supply chain.</p> <p>“We do not operate in isolation,” he said, pointing to the bank’s reliance on software vendors and its supplier relationships with Wall Street counterparties. “That entire ecosystem is only as strong as the weakest link.”</p> <p>Ultimately, Garrido argued that AI will handle the laborious data crunching, such as analysing a client's risk appetite and market performance, so that human relationship managers can spend more time advising their clients.</p> <p>Looking ahead, Garrido predicts a future where AI becomes so integral to business operations that dedicated executive roles for AI may become obsolete.</p> <p>“There’s not going to be a head of AI,” Garrido said, adding that just as compute is now embedded in everyday life, AI will soon just be the way business is done. “It’s still a little bit of a retrofit, still getting into an existing process, and that’s going to go away. Start thinking AI first, rather than as an afterthought.”</p> <div class="pro-features-wrapper"></div> <div class="extra-info"> <div class="extra-info-inner"> <h3 class="splash-heading">Read more about AI in APAC</h3> <ul class="default-list"> <li>Digital Realty’s CTO <a href="https://www.computerweekly.com/news/366641232/Digital-Realty-CTO-on-AI-tokenomics-and-datacentre-infrastructure">talks up the pace of AI silicon innovation</a>, the growth of inferencing workloads, and why boasting about datacentre megawatts misses the point.</li> <li>DayOne and Cortical Labs are <a href="https://www.computerweekly.com/news/366639849/Neurons-over-silicon-Singapore-plans-first-biological-datacentre">bringing ‘wetware’ computing to Singapore</a>, using living neurons grown from stem cells to support the demand for AI while addressing sustainability concerns.</li> <li>Singtel and Nvidia have teamed up on a multimillion-dollar facility to <a href="https://www.computerweekly.com/news/366639492/Singtel-Nvidia-to-help-scale-enterprise-AI-deployments">help organisations scale enterprise AI deployments</a>, tackle extreme datacentre power densities, and prepare for the era of embodied AI.</li> <li>The Australian government has struck a major <a href="https://www.computerweekly.com/news/366639595/Australia-inks-five-year-deal-with-Microsoft-to-drive-AI-and-cloud-adoption">five-year volume sourcing agreement with Microsoft</a> to speed up adoption of AI and cloud technologies across the public sector.</li> </ul> </div> </div> Standard Chartered’s technology and security chief, Alvaro Garrido, says AI will transform finance, but the industry’s biggest vulnerabilities lie outside its own walls https://cdn.ttgtmedia.com/visuals/ComputerWeekly/HeroImages/Standard-Chartered-office-London-PR-hero.jpg https://www.computerweekly.com/news/366641549/In-the-AI-race-a-global-bank-bets-on-the-human-touch Mon, 13 Apr 2026 05:14:00 GMT 60 editor@computerweekly.com