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Emerging technologies: How can you cut through the noise?

Technology leaders need to focus the raw potential of emerging technology into a set of priorities with measurable, tangible business impacts

Technology has moved far beyond desktop devices and software upgrades. It now incorporates data analysis, augmented reality, and reimagining products as services. In fact, the range of recent advances – from nanotech to robotic process automation – can seem overwhelming to any IT professional.

Companies must sift through the promotional noise to find those emerging technologies that offer real potential. It’s not about chasing every shiny new object; it’s about translating the raw potential of that emerging technology into a focused set of priorities with measurable, tangible business impact.

One example of this, analysed in Deloitte’s 2017 Tech Trends report, is the emergence of machine intelligence. Despite attracting much attention over recent months, the reality is that artificial intelligence – technologies capable of performing tasks that normally require human intelligence – is only one part of a larger, more compelling set of developments in the realm of cognitive computing. The bigger story is machine intelligence – an umbrella term that includes machine learning, deep learning, robotics process automation and bots.

In practical terms, enabled by data, machine intelligence can augment employee performance, automate increasingly complex and more mundane workloads, and develop “cognitive agents” that simulate both human thinking and engagement. It allows technology leaders to move from a legacy world of retrospective data analysis to one in which systems make inferences and predictions. The ability to take these insights, put them into action and then use them to automate tasks and responses represents the beginning of a new cognitive era.

We are already seeing early, high-impactful cases for machine intelligence emerge in various sectors. For example, some hospitals in the US are beginning to “train” their machine intelligence systems to analyse billions of patient records. And in some financial services companies, cognitive sales agents are using machine intelligence to parse natural language to understand customers’ questions, handling up to 27,000 conversations simultaneously in a range of languages.

Another trend that has significant potential is what we call “blockchain: trust economy”. Blockchain, the shared ledger technology, is no longer just linked to crypto currencies such as bitcoin. Instead, it is emerging as the backbone for digital identities in the emerging “trust economy.”

Protocols disrupted

The latter refers to a world where existing trust protocols from banking systems and credit rating agencies that make transactions between parties possible, are being disrupted. For example, ride-sharing apps depend on customers publicly ranking drivers’ performance. And individuals open their home to paying lodgers based on the recommendations of other homeowners who have hosted the same person. We are growing accustomed to the notion that positive comments appearing under an individual’s name mean that we can also trust that person.

Beyond establishing trust, blockchain makes it possible to share information selectively with others to exchange assets safely and efficiently and – perhaps most promisingly – to proffer digital contracts. This transforms reputation into a manageable attribute.

In the next 18 to 24 months, entities across the globe are likely to explore blockchain opportunities that involve some aspects of digital reputation. This has the potential to rewire the financial industry and beyond, generating cost savings and new revenue opportunities.

These are only two examples of trends we expect to transform the way we all do business. Those leaders who can cut through the noise and harness the latest trends in technology will be better positioned to shape their company’s future and make an impact that matters.


Mark Lillie is technology strategy and global CIO programme leader at Deloitte. .................................................................................. ......................................................................................

This was last published in April 2017

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