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Primer: Make sense of cognitive computing

Bob Violino | June 6, 2017
If you’re confused about exactly what it means from an IT and business perspective, you’re not alone.


Which industries are most likely to be affected by the emergence of cognitive technologies?

The financial services sector today is showing the greatest interest in cognitive technologies, Andrews says. “We see elevated levels of inquiry, searches on our website, and social media signals from and about financial services and AI,” he says. “Data in financial services is of greater volume and quality than it is in most verticals. That makes it ripe for advanced analytical strategies.”

But cognitive computing’s potential has applicability across just about every major industry that relies on data-driven decision-making to improve outcomes; where efficiency and accuracy gains can be realized through the automation of some processes; and where mass-consumer personalization at scale is required, Deloitte’s Roma says.

“Any industry where data is gathered and can be used to gain insights will be affected,” IBM’s Greenstein adds. “Cognitive technologies can open new markets, deliver efficiencies, and deliver competitive advantage by delivering real-time insights that are actionable.”

In sectors such as financial services, health care, manufacturing, legal, and public sector, competitiveness is increasing their dependence on “finding that needle in the haystack faster so they can improve their quality and timeliness of their actions,” says Brian Cowe, a senior product manager at Hewlett Packard Enterprise.


What are some of the major challenges with cognitive computing?

Some of the biggest challenges revolve around transparency of decision-making based on data, as well as its trustworthiness, IDC’s Schubmehl says. “Organizations also have to be careful of providing too much information and/or decision-making that the product or service becomes unattractive to the consumer or user,” he says.

To gain the biggest benefit possible from cognitive technologies, enterprises need the ability to connect and combine all their internal data with that of public data, Greenstein says.

“This presents a challenge, given the volume of data created each day in any given industry and the fact that it is often siloed in various locations,” Greenstein says. “Add to that the fact that up to 80 percent of business data is not searchable. This is why it is so critical that enterprises go through a digital transformation, embracing the data of their own business and the world around them.”


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