Copyright TechTarget - All rights reserved ComputerWeekly’s best articles of the day https://cyber.law.harvard.edu/rss/rss.html Techtarget Feed Generator en Thu, 14 May 2026 04:16:02 GMT https://www.computerweekly.com editor@computerweekly.com <p>For a while now, gamers have shouted at their screens, barking orders or venting frustrations at virtual squadmates who could not hear them. In the rare games that did incorporate voice commands, players were forced to memorise rigid menus containing specific phrases.</p> <p>But at the <a href="https://www.computerweekly.com/news/366640398/Nvidia-expands-Vera-Rubin-platform-details-Groq-integration">Nvidia GTC 2026 developer conference</a> earlier this year, French video game giant Ubisoft offered a glimpse into a future where onscreen characters can understand what you are saying – and talk back – through Teammates, an experimental prototype that replaces traditional, pre-programmed non-playable characters (NPCs) with squadmates powered by <a href="https://www.computerweekly.com/news/366612652/APAC-organisations-embrace-generative-AI">generative artificial intelligence (GenAI)</a>.&nbsp;</p> <p>Expanding on Ubisoft’s 2024 Neo NPC project, which was honoured under the France 2030 programme for advancing French innovation, Teammates places players in a first-person shooter alongside virtual soldiers who react to natural language, environmental context and the player’s personal slang.</p> <p>Tell your virtual teammate, “Find cover behind that car and wait for my order to shoot the closest enemy”, and the character will parse the command, evaluate its surroundings, and execute the manoeuvre while acknowledging the strategy.</p> <p>According to Ubisoft, achieving this level of immersion required more than just powerful <a href="https://www.computerweekly.com/feature/LLMs-explained-A-developers-guide-to-getting-started">large language models (LLMs)</a>. The project team had to rethink the inference pipeline to abstract complexity and optimise for latency.</p> <section class="section main-article-chapter" data-menu-title="Abstracting complexity"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Abstracting complexity</h2> <p>Behind the scenes, the goal is not just to build an AI-powered game but to build a foundation that thousands of artists, writers and designers can use without needing a background in <a href="https://www.computerweekly.com/resources/Artificial-intelligence-automation-and-robotics">AI and machine learning</a>.</p> <p>“Most game development teams don’t have all the specialised skills required to update complex GenAI systems,” Joel Gregoire, technical director at Ubisoft Paris, explained during the GTC presentation. “The answer to that question was to build a platform to abstract the complexity and make games with GenAI features.”</p> <p>Ubisoft’s solution functions as an agnostic middleware. Built around a C++ software development kit, the platform creates gameplay building blocks, such as NPC interactions, which are dynamically translated into prompts. Through custom engine plugins, this data feeds directly into Ubisoft’s proprietary Snowdrop and Anvil engines, translating raw language model outputs into engine-specific formats like facial animation data.</p> <p>“Think of it as an agnostic middleware for GenAI that we can easily plug into our in-house game engines,” said Xavier Manzanares, director of gameplay GenAI at Ubisoft. “It opens a whole lot of new opportunities for our teams.”</p> </section> <section class="section main-article-chapter" data-menu-title="The problem of the awkward pause"> <h2 class="section-title"><i class="icon" data-icon="1"></i>The problem of the awkward pause</h2> <p>If the promise of conversational AI in gaming is exciting, the engineering required to make it convincing is formidably complex. For all their linguistic fluency, LLMs are computationally heavy and notoriously slow.</p> <div class="pro-features-wrapper"></div> <blockquote class="main-article-pullquote"> <div class="main-article-pullquote-inner"> <figure> Most game development teams don’t have all the specialised skills required to update complex GenAI systems. The answer was to build a platform to abstract the complexity and make games with GenAI features </figure> <figcaption> <strong>Joel Gregoire, Ubisoft Paris</strong> </figcaption> <i class="icon" data-icon="z"></i> </div> </blockquote> <p>In a normal conversation, a human responds in a fraction of a second. When Ubisoft began testing its early generative models, the characters took more than three seconds to process a player’s speech, decide on an action, generate a response, and synthesise the audio.</p> <p>“Creativity starts with quality,” Maxime Sazadaly, the technical lead machine learning engineer at Ubisoft Paris, told the audience at Nvidia GTC. “But in fact, there’s something almost as important as quality, and that’s latency.”</p> <p>A three-second delay in the middle of a virtual firefight could leave the player staring at a blank, unresponsive avatar. “Even if the action is the correct one, you won’t have a perception of intelligence just because it takes so long,” Sazadaly noted.</p> <p>To make the characters feel alive, Ubisoft’s engineers determined that the entire loop – from a player speaking into a microphone to a character reacting – had to occur in under two seconds, which the team set out to achieve in three ways:</p> <ol class="default-list"> <li><b>Using faster base models:</b> The team switched from slower models to more efficient ones, employing Nvidia’s Parakeet-tdt-v3 for automatic speech recognition (ASR), Gemini 2.5 Flash Lite for cloud LLM inference, and ElevenLabs Flash v2 for text-to-speech (TTS).</li> </ol> <ol start="2" class="default-list"> <li><b>Streaming everywhere:</b> Instead of waiting for an entire response to generate, Ubisoft implemented partial function parsing. The moment the LLM outputs its first actionable function, the data is pushed to the game’s behaviour tree so the NPC can start moving. Audio is similarly streamed and stitched together chunk by chunk.</li> </ol> <ol start="3" class="default-list"> <li><b>Prompt factorisation:</b> By identifying redundant aliases and data in their massive 10,000+ token perception prompts, the team reduced prompt sizes by 30%, significantly lowering the time-to-first-token (TTFT).</li> </ol> <p>As a result of these optimisations, the team reduced the response time to just 1.5 seconds.</p> <p>Gregoire’s team also established an <a href="https://www.computerweekly.com/feature/Enterprise-strategies-for-API-management">application programming interface</a> (API) gateway that lets developers perform inference in the cloud, accessing third-party models or Ubisoft-hosted models via Kubernetes and Nvidia graphics processing unit (GPU) operators – or entirely on-device to enable offline play and lower operational costs.</p> <p>Using <a href="https://developer.nvidia.com/rtx/in-game-inferencing">Nvidia In-Game Inferencing</a> and Cuda-in-Graphics integrations, the team successfully deployed Teammates locally on high-end consumer GPUs: the Nvidia RTX 4090 and RTX 5090. To stay within a typical AAA game’s rendering budget, they also used highly optimised <a href="https://www.computerweekly.com/feature/Early-days-for-small-language-models-and-AI-at-the-edge">small language models (SLMs)</a>, specifically the four-billion-parameter Qwen3-4B-Instruct-2507 model quantised to INT4 for speed and FP8 for quality, and the KaniTTS-400m model for local voice generation.</p> <p>“Current high-end hardware and optimised inference stacks now allow multi-model GenAI pipelines to run alongside game workloads,” said Gregoire. “Moving the inference on-device is the next logical step to make NPC interaction scalable.”</p> <p>The prototype also includes the Jaspar AI personal assistant that helps players navigate game menus, adjusts the interface for accessibility needs, like colour blindness, and offers tactical advice. Furthermore, the game’s AI constantly analyses the player’s behaviour, awarding dynamic achievements based on their playing style and providing a personalised debriefing at the end of each mission.</p> <p>Whether Ubisoft’s project will progress further to entirely replace the hand-crafted, cinematic moments that have defined blockbuster games remains to be seen. For now, the industry’s largest players view AI as a tool to bolster the gaming experience.</p> <p>“Creativity remains deeply human,” said Yves Guillemot, the co-founder and chief executive of Ubisoft. “AI provides tools that help bring creative visions to life in new ways; it can be a powerful enabler to create even more meaningful and immersive experiences for players.”</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>With half of all GenAI projects failing after the proof-of-concept stage, organisations are discovering that technology alone isn’t a silver bullet. Here’s <a href="https://www.computerweekly.com/opinion/Why-50-of-GenAI-projects-fail-and-how-to-beat-the-odds">how to turn them into lasting competitive advantages</a>.</li> <li><a href="https://www.computerweekly.com/news/366642824/Nutanix-CEO-maps-out-agentic-AI-strategy-targets-VMware-defectors">Nutanix CEO Rajiv Ramaswami</a> talks up the company’s agentic AI play, the growing demand for sovereign cloud capabilities, and why decoupling storage from HCI is hastening migrations from VMware.</li> <li>At Qualtrics Experience Live in Sydney, leaders from Zip Co, Fonterra, Swyftx and Commonwealth Bank shared <a href="https://www.computerweekly.com/news/366642772/ANZ-enterprises-turn-to-AI-for-customer-and-employee-insights">how AI is accelerating research, breaking down data silos and turning feedback into measurable business value</a>.</li> <li>Monday.com’s <a href="https://www.computerweekly.com/news/366642592/Mondaycom-targets-third-wave-of-AI-with-OpenClaw-service">Globster service brings OpenClaw to consumers and businesses</a> in a bid to democratise access to agentic AI capabilities.</li> </ul> </div> </div> </section> Ubisoft executives offer a glimpse into the engineering behind its generative AI middleware, including the use of small language models, prompt optimisation and on-device processing to bring virtual teammates to life https://cdn.ttgtmedia.com/visuals/ComputerWeekly/HeroImages/gaming-gamer-gamification-training-sezer66-adobe.jpg https://www.computerweekly.com/news/366642940/In-video-games-of-the-future-your-AI-teammates-will-actually-listen Tue, 12 May 2026 05:15:00 GMT <p>When technology giants look to build the large datacentres required to power the internet and the <a href="https://www.computerweekly.com/news/366630422/AI-boom-to-push-Australian-IT-spending-past-A172bn">artificial intelligence (AI) boom</a>, their primary concern is not necessarily real estate, climate or tax incentives – it’s finding enough electricity.</p> <p>With Deloitte projecting <a href="https://www.deloitte.com/ap/en/perspectives/powering-asia-pacific-data-centre-boom.html">$800bn worth of datacentre investments in Asia-Pacific</a> by 2030, the availability of power has become the single most decisive factor in the region’s digital economy, according to Jean-Christophe Moureau, senior vice-president for solutions operations at Schneider Electric, a multinational company specialising in digital automation and energy management.</p> <p>“The criteria for selecting where to build a datacentre today is where we have energy,” he said in a recent interview with Computer Weekly. “And the expansions make it even more difficult, because Microsoft, Google and all the Big Tech companies are looking at developing datacentres but the energy is not there.”</p> <p>The scale of the challenge is unprecedented: global energy demand for datacentres, which was 460 terawatt-hours in 2022, is expected to reach over 1,000 terawatt-hours by 2026, according to an <a href="https://iea.blob.core.windows.net/assets/6b2fd954-2017-408e-bf08-952fdd62118a/Electricity2024-Analysisandforecastto2026.pdf">International Energy Agency (IEA) report</a>.</p> <p>Across the region, the power squeeze has already affected datacentre buildouts. Moureau noted that in Singapore, a major technology hub, energy limitations have forced delays for projects from companies such as Meta.</p> <p>“The Singapore government just said, ‘Look, sorry guys, we don’t have energy for you before 2028’,” he added.</p> <p>Against this backdrop, more datacentre operators are taking power generation into their own hands, investing in <a href="https://www.techtarget.com/searchdatacenter/tip/Pros-and-cons-of-on-site-power-generation-for-data-centers">on-site generators</a>, microgrid architectures and battery energy storage systems. In the US, major players are exploring dedicated energy parks and <a href="https://www.techtarget.com/searchdatacenter/tip/How-to-implement-nuclear-energy-for-data-centers">small modular reactors</a> to secure a steady power supply.</p> <section class="section main-article-chapter" data-menu-title="Greenfield builds"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Greenfield builds</h2> <p>In markets with untapped power potential, datacentre operators and hyperscalers are eyeing greenfield builds.</p> <p>In India, for example, multinational conglomerate <a href="https://www.reuters.com/world/india/tech-majors-commit-billions-dollars-india-ai-summit-2026-02-19/">Reliance Industries is investing $109.8bn to build AI datacentres</a>, while Microsoft is slated to open its fourth and largest datacentre region in the subcontinent later this year.</p> <p>The Middle East, specifically Saudi Arabia and the Gulf states, has also <a href="https://www.computerweekly.com/feature/Middle-East-datacentre-capacity-set-to-triple-by-2030">become a datacentre hotspot</a>, with developers increasingly proposing gigawatt-scale mega-campuses backed by sovereign wealth funds.</p> <p>Moureau noted that while new investors can “put a billion on the table in five minutes”, they lack a deep, technical understanding of datacentre operations, relying on engineering partners to translate capital into viable infrastructure.</p> </section> <section class="section main-article-chapter" data-menu-title="Optimising datacentre efficiency"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Optimising datacentre efficiency</h2> <p>The power crunch is driving the industry to optimise datacentre efficiency. At Schneider Electric, engineers are trying to tear down traditional silos of datacentre construction.</p> <div class="pro-features-wrapper"></div> <p>Historically, cooling systems, IT infrastructure and electrical distribution were designed independently, but today, they must be deeply integrated and digitally monitored to shave off every possible kilowatt of wasted energy.</p> <p>One promising development is direct current (DC) power. While much of the world runs on alternating current (AC) power, converting AC to DC results in significant energy loss.</p> <p>Some players, such as ST Telemedia Global Data Centres (STT GDC), are <a href="https://www.computerweekly.com/news/366637683/STT-GDC-launches-HVDC-testbed-to-address-AIs-power-demands">piloting DC-powered datacentres</a> – a move Moureau believes could bring significant efficiency gains, drawing on his own background managing DC energy systems for submarines.</p> <p>On a macro level, geopolitical and supply chain hurdles loom large. The transition to green energy has been uneven, and the energy crisis sparked by geopolitical conflicts has led some countries to reopen coal-fired power plants. Moureau called the return to coal “the biggest failure of strategy we can face today”, adding that sustainability must remain the industry’s north star, relying more on solar energy, battery storage and microgrids.</p> <p>The biggest impediment to datacentre expansion, however, is human capital. The specialised nature of modern datacentres has created a severe labour shortage that threatens to slow development just as much as a lack of electricity.</p> <p>“We talk about energy and a lot of things, but we never talk about people,” said Moureau. “To find a cooling expert in the market is not easy. Piping is not mathematical; it’s heuristic. You need years of experience. Just try to find good welders.”</p> <div class="extra-info"> <div class="extra-info-inner"> <h3 class="splash-heading">Read more about datacentres in APAC</h3> <ul class="default-list"> <li>With AI spurring gigawatt-scale datacentre builds across APAC, <a href="https://www.computerweekly.com/news/366641460/Optical-networks-to-bridge-the-AI-compute-consumption-gap">Ciena is deploying ultra-fast, energy-efficient optical networking</a> and AI-driven automation to ensure AI services can reach consumers.</li> <li>Digital Realty's CTO talks up the pace of AI silicon innovation, the growth of inferencing workloads, and why <a href="https://www.computerweekly.com/news/366641232/Digital-Realty-CTO-on-AI-tokenomics-and-datacentre-infrastructure">boasting about datacentre megawatts misses the point</a>.</li> <li>The APAC region is leading a global datacentre expansion, but surging energy demands and the risk of outages will require datacentre operators to adopt <a href="https://www.computerweekly.com/opinion/Why-proactive-asset-management-is-mission-critical-for-APAC-datacentres">proactive strategies to ensure a resilient and sustainable digital future</a>.</li> <li>At Gitex Asia 2025, industry leaders discuss how the computational demands of advanced AI models are forcing a <a href="https://www.computerweekly.com/news/366623023/How-AI-workloads-are-reshaping-datacentre-design">rethink of datacentre power, cooling and networking</a> infrastructure.</li> </ul> </div> </div> </section> A projected $800bn datacentre infrastructure investment in APAC alone is clashing with the limits of global power grids, forcing datacentre operators to rethink where and how they build the physical engines of the internet https://cdn.ttgtmedia.com/visuals/ComputerWeekly/Hero%20Images/datacentre-blue-fotolia.jpg https://www.computerweekly.com/news/366642996/Inside-the-global-datacentre-squeeze Mon, 11 May 2026 04:45:00 GMT <p>Australian organisations are expected to spend more than A$33.6bn on public cloud services in 2026, an increase of 17.9% from 2025, according to the latest forecast from technology research firm Gartner.</p> <p>Driven by the <a href="https://www.computerweekly.com/news/366627559/AI-adoption-grows-amid-falling-trust-in-AI-outputs">growing adoption of artificial intelligence</a> (AI), <a href="https://www.computerweekly.com/resources/Infrastructure-as-a-Service-IaaS">infrastructure as a service</a> (IaaS) is forecast to record the fastest growth among the main cloud segments, rising 24.1% to A$7.1bn. This will be closely followed by platform as a service (PaaS) at 20.9%.</p> <p>“AI-driven demand for high-performance cloud infrastructure is changing how Australian organisations are prioritising cloud spending this year,” said Adrian Wong, director-analyst at Gartner.</p> <p>“While AI compute demands are driving rapid IaaS growth, the ultimate goal for Australian organisations is business value. As the market shifts <a href="https://www.computerweekly.com/news/366627053/Enterprise-AI-adoption-moving-beyond-experimentation">from early AI experimentation to real-time inference and agentic AI</a>, organisations are relying heavily on robust PaaS environments to manage autonomous workflows and integrate them into core applications,” he added.</p> <p>Software as a service (SaaS) remains the largest spending category for Australian organisations in 2026, forecast to reach almost A$16.4bn. However, its 13.8% increase represents a slight slowdown in growth compared with 2025 as the market matures. Organisations are increasingly prioritising licence optimisation, absorbing slower seat growth and applying tighter scrutiny to their application portfolios.</p> <section class="section main-article-chapter" data-menu-title="Hyperscaler investments fuel local capacity"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Hyperscaler investments fuel local capacity</h2> <p>The continued surge in Australian cloud spending aligns with massive recent infrastructure investments from global hyperscalers eager to turn the country into a regional AI and cloud hub.</p> <p>In June 2025, Amazon Web Services (AWS) announced a record A$20bn investment to expand its datacentre infrastructure in Sydney and Melbourne between 2025 and 2029. The expansion is aimed at supporting complex AI workloads, supercomputing applications, and national security requirements.</p> <p>AWS’s investment follows <a href="https://www.computerweekly.com/news/366556772/Microsoft-to-invest-A5bn-in-Australia">Microsoft’s A$5bn commitment in late 2023</a> to expand its computing capacity by 250% and grow its hyperscale and AI infrastructure footprint to 29 datacentre locations across the country.</p> <p>As Australian organisations mature in their AI journey, more of them are gearing towards inference-optimised infrastructure as they fine-tune smaller, domain-specific models instead of relying on general-purpose large language models. “Many are turning to hybrid cloud architectures to push this processing to the edge, which lowers cloud costs while still supporting automation at scale,” Wong said.</p> <p>One of the AI applications that can benefit from inference-optimised infrastructure is agentic commerce, where virtual agents have reasoning capabilities to understand context, identify complex needs and act on behalf of the customer.</p> <p>In April 2026, Australian hardware chain <a href="https://www.computerweekly.com/news/366642113/Bunnings-shows-off-AI-shopping-agent-at-Google-showcase">Bunnings launched Buddy</a>, an AI-powered shopping assistant that provides customers with expert advice and helps them find what they need. Built with Google Cloud’s Gemini Enterprise for CX platform in just over six weeks, the tool combines Google AI and infrastructure with Bunnings’ deep product expertise to transform the e-commerce experience from “product search to project search”.</p> <p>Following its progressive roll-out on Bunnings’ 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>The retailer 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> <div class="extra-info"> <div class="extra-info-inner"> <h3 class="splash-heading">Read more about cloud and 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 <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>ANZ Bank has started <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> to help business bankers recover hours of lost productivity by automating tasks and streamlining workflows.</li> <li>Oracle has <a href="https://www.computerweekly.com/news/366640566/Oracle-opens-Sydney-customer-excellence-centre-to-boost-AI-adoption">opened an AI customer excellence centre in Sydney</a> to help its customers across Australia and Oceania adopt the technology.</li> </ul> </div> </div> </section> As hyperscalers such as AWS and Microsoft pour billions into Australian datacentres, Gartner predicts local public cloud spending will grow by 17.9% in 2026, driven by the growth in AI infrastructure demands https://cdn.ttgtmedia.com/visuals/ComputerWeekly/Hero%20Images/Australia-digital-flag-fotolia.jpg https://www.computerweekly.com/news/366642685/Australian-public-cloud-spending-to-surpass-A336bn-in-2026 Mon, 11 May 2026 04:41:00 GMT <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>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><a href="https://faq.whatsapp.com/820124435853543">WhatsApp’s use of encryption technologies</a> has significantly strengthened the privacy of its users, but the design of the popular messaging app also exposes them to a different class of client-side threats.</p> <p>That is according to Tal Be’ery, co-founder and chief technology officer of cryptocurrency wallet maker Zengo, who noted that WhatsApp remains a prime target because of its scale and the value of the data it protects, rather than any inherent weakness in its security.</p> <p>“WhatsApp is the gorilla of instant messaging. It is by far the most popular, with more than three billion users in all geographies,” said Be’ery said during his presentation at Black Hat Asia 2026 in Singapore, adding that just as crooks follow the money in bank robberies, a hacker would hack WhatsApp for the data.</p> <p>Be’ery explained that WhatsApp’s adoption of end-to-end encryption in 2016, based on the <a href="https://open-source%20Signal%20protocol">open-source Signal protocol</a>, was a major security improvement. Because messages are encrypted on the sender’s device and can only be decrypted on the recipient’s device, WhatsApp’s servers cannot read message content.</p> <p>Instead, the servers act as a “dumb pipe” that passes encrypted messages along, unable to inspect content, detect malicious traffic or intervene in individual sessions. This reduces the risk of mass surveillance and makes the servers a less useful target for attackers.</p> <p>However, this creates a trade-off. “WhatsApp is playing with a hand tied behind its back, because it cannot see the content,” said Be’ery. “The difference is Gmail can use the content of an email to decide to put on an alert, but WhatsApp’s server cannot do that – it can only use metadata.”</p> <p>This metadata includes whether one number is messaging too many people, whether multiple users are reporting the same account, or when an account generally behaves suspiciously. As a result of the server being protected, attackers are increasingly shifting their focus from the WhatsApp’s infrastructure to users’ devices, where messages are decrypted and can be accessed directly.</p> <p>Furthermore, the metadata that exists outside the message body can pose stalking and privacy risks. This includes information such as who messaged whom, when a message was sent, whether it was delivered, how many devices are linked, whether a device is online and potentially what type of device is being used.</p> <p>Be’ery noted that this is hard for users to control because delivery receipts are a core part of how WhatsApp functions. Even if a contact is subsequently blocked, a sender may have already gathered this intelligence.</p> <p>He also highlighted the threat of silent pings that allow an attacker to monitor when a device is online without visibly sending messages. This enables the attacker to infer behavioural patterns, such as identifying a user’s primary device, or tracking when they are travelling, online or offline.</p> <p>WhatsApp’s multi-device architecture – where a user may have a primary phone and several linked companion devices, such as WhatsApp Web or desktop clients – also creates new vulnerabilities. Be’ery argued this enables device enumeration, allowing an attacker to identify the number of devices linked to a target account; and device pinpointing, where they can target a specific device rather than sending the same payload to all of them.</p> <p>As attackers increasingly focus on metadata, delivery signals and the endpoint, sophisticated threat actors can chain multiple vulnerabilities together to launch <a href="https://www.techtarget.com/searchsecurity/news/366569061/Google-Spyware-vendors-are-driving-zero-day-exploitation">zero-click spyware attacks</a>. Delivered through files, link previews, groups, or device-sync features, these require no interaction from the victim. He cited a recent campaign that targeted 90 Italian WhatsApp users, including journalists and civil society members, using spyware developed by Paragon Solutions, an Israeli spyware company.</p> <p>While Be’ery said some of these issues have already been reported to Meta, resulting in partial fixes on certain platforms, more needs to be done. “What was good enough in 2016 is not good enough in 2026, when they have more than three billion users,” he said. “The security architecture needs to evolve.”</p> <p>One proposed solution is a lockdown mode that would only allow known contacts to send messages or rich media directly to a user. This would reduce the attack surface from billions of WhatsApp users to just those in a person’s address book.</p> <p>“If only my contacts can send to me, then all these silent pings from 3.5 billion potential attackers go away,” he said. “It does not solve the issue, but it greatly reduces it.”</p> <p>He also suggested implementing a limited message request model for unknown senders, similar to features on other social platforms, where strangers can only send restricted text requests rather than rich media or complex message types.</p> <p>Another fix involves obfuscating a user’s linked devices from the sender. Instead, the sender would interact with a single recipient identity, and the recipient’s own devices would synchronise the messages internally.</p> <p>“The main idea is not to expose all of the devices to the sender,” said Be’ery. “As a result, there is no more reconnaissance of the number of devices, and you cannot pinpoint a specific device.”</p> <p>Concluding his presentation, Be’ery stressed that WhatsApp’s end-to-end encryption remains vital but noted that every security design involves compromises. “WhatsApp end-to-end encryption protects the server, but exposes the client,” he said. “Unfortunately, there is no current solution the user can get out of this talk and apply.”</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> The use of encryption helps to secure WhatsApp’s infrastructure, but researchers at Black Hat Asia warn platform’s architecture is driving hackers to target user devices directly https://cdn.ttgtmedia.com/visuals/ComputerWeekly/Hero%20Images/Whatsapp-Facebook-Instagram-apps-Ed-Use-Only-adobe-hero.jpg https://www.computerweekly.com/news/366642369/WhatsApps-encryption-protects-servers-but-leaves-users-exposed-to-client-side-attacks Tue, 28 Apr 2026 22:54:00 GMT <p>For decades, enterprise software has acted as a digital filing cabinet or system of record where human workers painstakingly log the daily operations of a business. Now, Oracle wants to flip that dynamic, turning its software into an autonomous engine that does the work itself.</p> <p>The move hinges on what the tech industry is calling <a href="https://www.computerweekly.com/feature/Moving-agentic-AI-from-innovation-theatre-to-enterprise-production">agentic artificial intelligence</a> (AI), where software agents with the ability to reason and collaborate can execute multi-step tasks with minimal human intervention.</p> <p>Speaking with Computer Weekly on the sidelines of Oracle AI World Tour Singapore, Rondy Ng, Oracle’s executive vice-president for applications development, noted that <a href="https://www.computerweekly.com/resources/Enterprise-resource-planning-ERP-software">enterprise resource planning</a> (ERP) systems are evolving from passive repositories of data into autonomous systems of outcome that execute tasks based on high-level business goals.</p> <p>However, Ng made it clear that Oracle’s latest AI innovations are exclusively reserved for its <a href="https://www.computerweekly.com/resources/Software-as-a-Service-SaaS">software-as-a-service</a> (SaaS) products, such as Oracle Fusion, which is used by about 70% of its applications’ customer base. Legacy, on-premise product lines remain in maintenance mode.</p> <p>“When people deployed those legacy applications from the past, they were heterogeneous,” he said. “They were not standard processes.</p> <p>“If you have data demarcated in different ways, you can build agents to recognise all the differences, but the effort of doing that and the likelihood of making mistakes and hallucinations are higher.</p> <p>“But if you’re on a relatively clean slate, you get faster results, better accuracy and more automation,” added Ng. “Our strategy is for people to go to SaaS. When you’re on SaaS, you can deploy AI much more efficiently.”</p> <section class="section main-article-chapter" data-menu-title="From generative AI to over 1,000 agents"> <h2 class="section-title"><i class="icon" data-icon="1"></i>From generative AI to over 1,000 agents</h2> <p>Oracle has been fleshing out its AI strategy over the past 18 months. It initially focused on embedding generative AI to help users draft text, such as performance reviews or financial report summaries. From there, it set out to build 50 specific-purpose AI agents.</p> <p>Today, that number has swelled to over 1,000 task-specific agents. To manage these agents, Oracle introduced AI Agent Studio within Fusion applications, allowing customers and system integrators, such as KPMG, Deloitte and PwC, to stitch agents together, modify them, and inject human-in-the-loop approvals for compliance.</p> <p>More recently, in March 2026, Oracle unveiled a <a href="https://www.computerweekly.com/news/366640725/Oracle-applications-chief-sees-enterprise-AI-agents-as-task-specific-helpers">new generation of agentic applications</a> spanning customer experience (CX), human capital management (HCM), finance and supply chain at the Oracle AI Summit in London.</p> <p>Traditionally, ERP systems served as systems of record that logged operational history and enforced policy. But with agentic applications, instead of people having to work through the data and determine the next steps, users can just prescribe a set of objectives, goals and performance indicators, said Ng.</p> <p>Using an accounts receivable department as an example, he said a manager could simply instruct AI agents to maintain a specific cash inflow level or target a specific days sales outstanding (DSO) metric. The agents will then work behind the scenes, analysing transactional activities and data to provide the manager with optimised strategies. Once a strategy is selected, the agents farm the required work out to human payment collectors, even generating call scripts based on a client’s payment history and ongoing disputes.</p> <p>“In this case, the agents are working together to interpret and reason the data,” said Ng. “It helps to make decisions and execute them. It’s a much more autonomous way of thinking about how you drive your business.”</p> </section> <section class="section main-article-chapter" data-menu-title="Governance and the future of per-seat licensing"> <h2 class="section-title"><i class="icon" data-icon="1"></i>Governance and the future of per-seat licensing</h2> <p>Addressing concerns around governance and data security, Ng said Oracle’s AI agents work directly and interact with Fusion applications through <a href="https://www.computerweekly.com/feature/Enterprise-strategies-for-API-management">application programming interfaces</a> (APIs). “Whatever guardrails that already exist in the apps are observed at the AI layer,” he said. “Agents are just doing the job on behalf of a particular person with a security profile.”</p> <div class="pro-features-wrapper"></div> <p>Oracle is also bolstering its internal operations with these tools, using agentic AI to build applications, handle first-line customer support and replace complex rule engines by allowing developers to simply describe desired system behaviours in natural language.</p> <p>But as AI agents take on more workloads, it raises questions about the future of traditional SaaS pricing, which has long been tied to the number of people or seats licensed to access the software. Currently, Oracle provides generous token allowances – around 30 million tokens across different large language models – for agentic applications without charging a premium for an AI version of its software.</p> <p>Ng acknowledged that if agentic applications eventually allow a finance department of 100 people to operate with only five, Oracle’s pricing model will have to adapt. “Today, we are charging by seats because there’s still a need to have accountants running reports, so the seats are not going away yet,” he said.</p> <p>“But down the line, let’s say in five years, if people start to reduce the number of seats, Oracle is not going to charge by the number of seats. But at this point, we’re not seeing a mass exodus of people from their contracts.”</p> <p>Amid the potential of agentic AI, Ng pushed back against suggestions that core ERP systems will become commoditised.</p> <p>“If you’re a $2bn company and you tell regulators that your general ledger is going to be all over the place, how do you go to the SEC and prove that you are financially compliant?” said Ng, referring to the US Securities and Exchange Commission. “That layer is not going away. It’s the experience and productivity layer, and how you interact with the data, that’s evolving.”</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 <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 Oracle rolls out a slew of agentic AI tools and applications, a senior company executive explains how enterprise workflows are changing and why software pricing models may be due for a shake-up https://cdn.ttgtmedia.com/visuals/ComputerWeekly/Hero%20Images/business-applications-5-fotolia.jpg https://www.computerweekly.com/news/366642385/Oracle-is-turning-corporate-software-over-to-AI-agents Tue, 28 Apr 2026 04:45:00 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><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>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 <p>In Moscow, <a href="https://www.computerweekly.com/resources/Artificial-intelligence-automation-and-robotics">artificial intelligence (AI)</a> has transcended its science fiction origins to become the backbone of urban management, provided the city retains sovereignty over its technology capabilities.</p> <p>Speaking at a <a href="https://gitexasia.com/agenda#:~:text=Russian-,Federation,-FREE">fireside chat at Gitex AI Asia 2026 in Singapore</a>, Sergey Cheremin, minister of the government of Moscow and head of the department for external economic and international relations, outlined the Russian capital’s use of AI across public services, while cautioning against over-reliance on foreign technology vendors.&nbsp;</p> <p>Managing a metropolis of 15 million people with a GDP exceeding $450bn demands an efficient digital ecosystem, Cheremin noted. Today, the city implements AI in more than 130 programmes, spanning traffic control, healthcare, education, waste management and construction.</p> <p>“AI for us is not science fiction or about <i>The Matrix</i>,” he told the audience, referring to the 1999 movie that predicted a world dominated by AI. “It’s really online management of all municipalities.”&nbsp;</p> <p>But as governments around the world race to build their computing capacities, Cheremin stressed that true security will only come from having true digital sovereignty.&nbsp;</p> <p>“For big megacities like Moscow, it’s very important to provide security for your infrastructure, and you cannot be dependent on a few companies or technical solutions,” he said. “You cannot allow the vendors to dictate how you are going to manage the city.”</p> <p>To mitigate these risks and protect against cyber attacks that could trigger catastrophic electricity blackouts or system failures, Cheremin said all strategic and sensitive technologies for Moscow are developed in-house by expert IT teams. “It’s not good to be isolated, but it’s also important to be sovereign so you’re not dependent on anyone,” he added.</p> <section class="section main-article-chapter" data-menu-title="From Moscow to Singapore"> <h2 class="section-title"><i class="icon" data-icon="1"></i>From Moscow to Singapore&nbsp;</h2> <p>Noting the importance of international knowledge-sharing, Cheremin recalled his first trip to Singapore in 2010 to study the city-state’s advanced intelligent transport management systems.&nbsp;</p> <p>Realising that foreign systems could not be transplanted into another city wholesale, Moscow studied other models from New York, London, Paris and Barcelona, among other cities, and engaged companies such as Siemens, Cisco and Thales, eventually creating a traffic management system tailored to its needs.</p> <p>Today, the city’s transport system uses AI to optimise traffic flow, reducing congestion and saving commuters up to 30% of travel time. Furthermore, subway access is now processed through automatic biometric billing, removing the need for traditional transport cards.</p> <p>Moscow has also deployed a massive security network of more than 260,000 CCTV cameras integrated into a single data-processing system. According to the minister, this has slashed the city’s crime rate by 90% over the past decade and reduced car thefts by 15 times.</p> <p>Beyond security and transport, AI has delivered economic and social returns for the city. In healthcare, <a href="https://www.techtarget.com/pharmalifesciences/feature/Exploring-AI-applications-in-radiology">AI-assisted radiology</a> can identify diseases and predict cancers with high accuracy, saving both time and money for Moscow’s healthcare system.</p> <p>In urban planning, Moscow has spent a decade building a <a href="https://www.techtarget.com/searcherp/definition/digital-twin">digital twin</a>, a virtual model of the city featuring more than 9,000 data layers, from underground infrastructure such as subway lines to district demographics, allowing planners to predict the impact of future construction projects.&nbsp;</p> <p>Despite his strong advocacy for digital sovereignty, Cheremin reiterated that Moscow is not turning its back on the global tech community. He pointed to city-to-city diplomacy, noting that Moscow actively shares its technological playbook with cities across Southeast Asia, China, India, Africa and Latin America.&nbsp;</p> <p>“We understand that the situation is difficult...and it becomes unpredictable sometimes,” he said, referencing global geopolitical tensions that make events such as Gitex vital for sharing technological experience.</p> <p>“We are really proud for several decades that we have a very good partnership with Singapore,” Cheremin said. With 80% of the world’s population expected to live in cities within two decades, he added, Moscow will continue to strengthen its partnerships with ASEAN and Chinese cities such as Beijing, Shanghai and Chengdu to build a stable urban platform.</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> </section> By ensuring strategic technology capabilities are developed in-house, megacities can protect their critical infrastructure from cyber threats and global unpredictability, says Moscow government minister https://cdn.ttgtmedia.com/visuals/ComputerWeekly/Hero%20Images/Moscow-Russia-1-fotolia.jpg https://www.computerweekly.com/news/366641555/Moscow-champions-digital-sovereignty-and-AI-driven-city-management Fri, 10 Apr 2026 01:59:00 GMT <p>As the post-Second World War rules-based order frays and geopolitical tensions spill over into the digital realm, maintaining stability in cyber space is no longer just an ideal, but an absolute necessity for modern life, said Singapore’s cyber security chief, David Koh.</p> <p>Speaking at the Gitex AI Asia 2026 conference, Koh, commissioner of cyber security and chief executive of the Cyber Security Agency (CSA) of Singapore, pointed to the <a href="https://www.techtarget.com/whatis/34-Cybersecurity-Statistics-to-Lose-Sleep-Over-in-2020">gloomy state of cyber security</a>, warning that the economic and societal benefits of artificial intelligence (AI) and the digital economy will “come to naught” if cyber space is not secure.</p> <p>“Without rules, all countries, perhaps with the exception of the great powers, will suffer amidst the destruction and chaos,” he told a gathering of tech leaders, government officials and IT professionals. “Cyber space is increasingly becoming unstable, threatened by escalating geopolitical tensions and rapidly evolving cyber threats. The outlook isn’t positive.”</p> <p>Globally, cyber threats surged by 47% in the first quarter of 2025 compared with the previous year, said Koh, citing data from Check Point, a cyber security technology supplier. The economic toll is equally staggering, with ransomware expected to inflict $74bn in damages globally this year – a figure that could reach $276bn by 2031.</p> <p>Singapore has not been immune to these threats. He noted a fourfold increase in advanced persistent threat (APT) attacks against the city-state between 2021 and 2024.</p> <p>The situation prompted the Singapore government to take decisive action last year. In 2025, it announced that its critical information infrastructure (CII) had been <a href="https://www.computerweekly.com/news/366638973/Singapore-mounts-largest-ever-cyber-operation-to-oust-APT-actor">targeted by the sophisticated APT actor known as UNC3886</a>.</p> <p>“We took the unprecedented step to name the threat actor so that we can crystallise the threat and educate our own public that our CIIs are under attack,” said Koh, stressing that Singapore’s own experience reveals a deteriorating and potentially dangerous state of cyber stability.</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&nbsp;<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&nbsp;<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>&nbsp;and business partners after hackers infiltrated its internal Slack messaging platform.</li> <li>Australian privacy commissioner warns that the&nbsp;<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>&nbsp;as notifications caused by staff mistakes rose significantly even as total breaches declined 10% from a record high.</li> <li>Philippine bank&nbsp;<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>&nbsp;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> <p>This worsening threat landscape is pushing nations to adjust their security postures, moving away from purely protective measures. “Concepts like active defence, forward defence, or even ‘hack back’, once uttered in closed policy circles or hushed tones, are now increasingly being heard openly,” said Koh.</p> <p>Such aggressive postures carry risks in the “fog of war” of the internet. “A single misinterpreted signal can trigger a vicious cycle of escalation and potentially spill over with unpredictable consequences,” he warned.</p> <p>To preserve cyber stability, Koh outlined three urgent calls to action for cyber leaders across government, academia and industry.</p> <p>First, he called for nations to keep channels of communication open and practice restraint to pre-empt escalation. “Dialogue is not just about people who are friends or who think alike,” said Koh. “We also need to have dialogue with people who we don’t quite agree with.”</p> <p>Second, he called for deeper cooperation between cyber agencies domestically and internationally, citing regional groupings such as the Association of Southeast Asian Nations and plurilateral platforms such as the <a href="https://www.techtarget.com/healthtechsecurity/news/366594169/40-Countries-Pledge-Not-to-Pay-Ransoms-at-International-Counter-Ransomware-Summit">Counter Ransomware Initiative</a> as vital enablers for collective security. By exchanging threat information and working together to disrupt common adversaries, states can achieve better outcomes than they could alone.</p> <p>Finally, Koh stressed the need to uphold existing international agreements, including the United Nations Charter and the 11 voluntary, non-binding norms for responsible state behaviour in cyber space.</p> <p>Acknowledging the scepticism some might have regarding the effectiveness of international law in today’s turbulent climate, he remained resolute. “We have to keep on trying and not give up,” said Koh. “Without it, everyone, all of us, will lose. Cyber stability is not a luxury. It’s not something that’s [just] nice to have, but increasingly it is a necessity for our modern way of life.”</p> <div class="pro-features-wrapper"></div> With state-linked attacks rising and international rules unravelling, Singapore’s cyber security commissioner calls for global cooperation to prevent catastrophic conflict in cyber space https://cdn.ttgtmedia.com/visuals/ComputerWeekly/Hero%20Images/Military-digital-defence-adobe.jpg https://www.computerweekly.com/news/366641228/Singapore-Cyber-Security-Agency-chief-Cyber-stability-a-necessity-not-a-luxury Thu, 09 Apr 2026 16:45:00 GMT <p><a href="https://www.computerweekly.com/resources/Artificial-intelligence-automation-and-robotics">Artificial intelligence (AI)</a> is often imagined as an ethereal network of algorithms and advanced computing chips in the cloud. But behind the scenes, the ability to generate a poem, render a video or run complex predictive models relies on pulses of light travelling through glass fibres across oceans and continents.</p> <p>As big tech firms and enterprises <a href="https://www.computerweekly.com/feature/Middle-East-datacentre-capacity-set-to-triple-by-2030">race to build multibillion-dollar datacentres</a> to fuel the demand for AI, the telecoms infrastructure connecting them is under immense pressure. This has created significant opportunities for companies such as Ciena, a global networking systems and software provider.</p> <p>“AI is only good when it is consumed,” said Amit Malik, vice-president and general manager of Ciena in Asia-Pacific, Japan and India. “We are the bridge between compute and consumption because we provide those pipes.</p> <p>“For a while, people thought we were the derivative layer, because we were getting the benefits of what’s happening on the upper layers in AI, but the world has started believing that we are the mission-critical layer because if the network is down, nothing flows,” he added.</p> <p>To meet the insatiable demand for bandwidth, Ciena has leaned heavily into its leadership in <a href="https://www.lightreading.com/cable-technology/cable-connects-with-coherent-optics">coherent optics</a>, which synchronises light waves to reduce noise and carry more data over long distances. Its flagship <a href="https://www.computerweekly.com/news/365531325/Ciena-claims-industry-first-with-16-Tbps-coherent-optic-service">WaveLogic 6 modem</a>, capable of transmitting data at 1.6 terabits per second, is currently the fastest in the world and has become an industry benchmark.</p> <p>This technology, already adopted by companies like Australia’s Telstra and India’s Vodafone Idea, consumes half the space and power of previous generations while offering ultra-low latency. This is particularly beneficial for datacentre and telecom operators that face stringent sustainability requirements.</p> <p>Ciena’s advancements have also extended to the servers powering AI. The company recently launched the Vesta 200 6.4T optical engine, which manages the complex electrical-to-optical conversions within datacentres. This innovation is propelling the industry’s <a href="https://www.lightreading.com/optical-networking/ofc-2026-optical-networking-s-ai-reckoning-arrives">transition towards photonics</a> as traditional copper and electrical systems approach their limits. “We do believe that the world is moving from electrons to photons,” Malik said.</p> <section class="section main-article-chapter" data-menu-title="APAC datacentre boom"> <h2 class="section-title"><i class="icon" data-icon="1"></i>APAC datacentre boom</h2> <p>The Asia-Pacific (APAC) region is seeing a staggering scale of infrastructure deployment, driven by hyperscalers establishing massive facilities closer to where most of the world’s data is generated.</p> <p>“The erstwhile datacentres used to be not very complex. If you were setting up a 30-megawatt datacentre, somebody would have said, ‘That's a huge datacentre.’ Today, <a href="https://www.techtarget.com/searchdatacenter/news/366627578/Meta-Google-unveil-massive-AI-data-center-investment-plans">one gigawatt seems to be the currency</a>,” Malik said.</p> <blockquote class="main-article-pullquote"> <div class="main-article-pullquote-inner"> <figure> For a while, people thought we were the derivative layer, because we were getting the benefits of what’s happening on the upper layers in AI, but the world has started believing that we are the mission-critical layer because if the network is down, nothing flows </figure> <figcaption> <strong>Amit Malik, Ciena</strong> </figcaption> <i class="icon" data-icon="z"></i> </div> </blockquote> <p>Growth projections for datacentre buildouts in APAC are being outpaced by reality. While analysts once predicted steady, incremental growth, the pace of development has accelerated dramatically.</p> <p>“Every time people imagine something, three months later, somebody else comes and announces gigawatt datacentres, which changes the whole figure,” Malik said. He highlighted recent announcements of four to five one-gigawatt facilities in India, along with significant investments in the Thailand-Singapore-Malaysia corridor, Japan, Korea and Australia.</p> <p>This regional momentum is clearly reflected in Ciena’s financial performance. During its fiscal Q1 2026 earnings call, Ciena reported a 40% year-over-year growth in orders from India. Additionally, geopolitical issues in the Middle East have spurred the creation of new subsea cable routes, highly benefiting strategic landing points in India and Australia.</p> </section> <section class="section main-article-chapter" data-menu-title="AIOps and autonomous networks"> <h2 class="section-title"><i class="icon" data-icon="1"></i>AIOps and autonomous networks</h2> <p>Operating networks that move petabytes of data across hundreds of fibre strands requires a new level of management capability. To address this, Ciena is embedding <a href="https://www.techtarget.com/searchitoperations/definition/AIOps">AI operations (AIOps)</a> across its software layers, including its Blue Planet platform, pushing the industry towards fully autonomous networks.</p> <div class="pro-features-wrapper"></div> <p>This AI-driven automation helps optimise wavelength selection for high-speed routing and allows for the predictive remediation of network issues before they occur. It also helps mitigate the tech sector’s talent shortage.</p> <p>“You don’t really have that many trained professionals everywhere,” Malik said, noting that Ciena's AI tools have significantly improved support efficiency, enabling service teams to resolve complex issues and even manage deployments remotely with fewer resources.</p> </section> <section class="section main-article-chapter" data-menu-title="AI sovereignty and supply chain crunch"> <h2 class="section-title"><i class="icon" data-icon="1"></i>AI sovereignty and supply chain crunch</h2> <p>As AI technologies mature, governments worldwide are increasingly focused on digital and AI sovereignty. Some are developing <a href="https://www.computerweekly.com/feature/Sea-Lion-explained-Southeast-Asias-first-large-language-model">indigenous large language models (LLMs) tailored to local languages</a> and cultural nuances while ensuring data protection.</p> <p>Although training these massive models entirely within national borders remains prohibitively expensive for many countries, localised inferencing is becoming more widespread. This requires heavily encrypted, sovereign networks, Malik noted.</p> <p>Looking ahead, Ciena is addressing future threats by deploying quantum-safe networking. The company recently demonstrated next-generation quantum-secured communications at the <a href="https://www.lightreading.com/optical-networking/ofc-2026-optical-networking-s-ai-reckoning-arrives">2026 Optical Fiber Communication Conference</a>.</p> <p>Despite the massive growth opportunities, the industry is not without its headwinds. The rapid expansion of hyperscalers has outpaced the global supply chain’s capacity, leading to shortages in fibre optics and semiconductor components.</p> <p>“Do we have enough fibre? The answer is no, and that is why you are seeing more fibre investments coming up,” Malik said, adding that supply chain bottlenecks for specialised tech components are also a concern.</p> <p>“Your constraint can be that last golden screw. You might have 99.9% of the equipment ready, but if one screw is missing because the supplier cannot scale, then you’re stuck,” Malik explained.</p> <div class="extra-info"> <div class="extra-info-inner"> <h3 class="splash-heading">Read more about AI infrastructure in APAC</h3> <ul class="default-list"> <li>NetApp’s regional chief <a href="https://www.computerweekly.com/news/366639344/APAC-firms-still-in-AI-test-mode-as-data-readiness-issues-persist">discusses the gap between AI intent and production</a>, the rise of neoclouds, and why the storage firm is counting on getting data AI-ready to win market share.</li> <li>Singtel, China Telecom and SK Telecom are <a href="https://www.computerweekly.com/opinion/How-APAC-telcos-are-reclaiming-relevance-with-AI-ready-infrastructure">pivoting away from head-on competition with hyperscalers</a> to become enablers of the AI era through sovereign cloud and edge platforms.</li> <li>In this <a href="https://www.computerweekly.com/ezine/CW-Asia-Pacific/CW-APAC-Trend-Watch-AI-infrastructure">handbook</a>, focused on AI infrastructure trends in the Asia-Pacific region, Computer Weekly looks at how it should be deployed, data and sustainability challenges and the advantages of large language models.</li> <li>Digital Realty’s CTO Chris Sharp talks up the <a href="https://www.computerweekly.com/news/366641232/Digital-Realty-CTO-on-AI-tokenomics-and-datacentre-infrastructure">pace of AI silicon innovation</a>, the growth of inferencing workloads, and why boasting about datacentre megawatts misses the point.</li> </ul> </div> </div> </section> With AI spurring gigawatt-scale datacentre builds across APAC, Ciena is deploying ultra-fast, energy-efficient optical networking and AI-driven automation to ensure AI services can reach consumers https://cdn.ttgtmedia.com/visuals/ComputerWeekly/Hero%20Images/digital-cables-fibre-optic-adobe.jpeg https://www.computerweekly.com/news/366641460/Optical-networks-to-bridge-the-AI-compute-consumption-gap Wed, 08 Apr 2026 01:25:00 GMT 60 editor@computerweekly.com