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TCS Leader Forecasts Rapid Adoption of Intelligent Apps in 2017

9 Rules for Digital Transformation in the Enterprise Various forms of machine learning algorithms are about to render entire classes of enterprise software obsolete as a new generation of intelligent applications capable of learning business processes starts to be rolled out in 2017. Dr. Satya Ramaswamy, global head of digital enterprise for Tata Consulting Services […]

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MV
Mike Vizard
Jan 4, 2017
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9 Rules for Digital Transformation in the Enterprise

Various forms of machine learning algorithms are about to render entire classes of enterprise software obsolete as a new generation of intelligent applications capable of learning business processes starts to be rolled out in 2017.

Dr. Satya Ramaswamy, global head of digital enterprise for Tata Consulting Services (TCS), says thanks to deep learning technologies made available via cloud services that employ graphical processing units (GPUs), for example, the cost of developing smarter applications is dropping substantially. Couple those capabilities with other advances in machine learning algorithms that can now be readily invoked via application programming interfaces (API), and Ramaswamy concludes that it should soon become feasible to democratize access to advances in machine learning algorithm technologies at rates that are unprecedented.

Making those technologies more broadly accessible, adds Ramaswamy, will in turn accelerate digital business transformation projects because rather than having to rely on static applications, a new generation of applications will continually learn from each user interaction. The result will be a rapid acceleration of digital business transformation projects based on a new generation of intelligent applications in 2017, says Ramaswamy.

In fact, Ramaswamy predicts that organizations that make use of machine learning technologies will focus as much of their efforts on creating entire new business models as they do re-engineering existing business processes.

“There will be a whole reimagining of customer experiences,” says Ramaswamy.

The rate at which these new intelligent applications are developed and deployed might be debatable in 2017. But the one thing that is for certain is that these applications are now feasible for a much broader range of organizations than ever before. Given the competitive nature of most industries, all it will really take is for one company in any vertical segment to create an intelligent application that provides a meaningful competitive advantage to prod the rest of that industry to follow suit.

In the meantime, IT organizations in 2017 would be well-advised to prepare for intelligent applications leveraging machine learning algorithms that at least have the potential to upend entire vertical industry segments. As Oscar Wilde once noted, expecting the unexpected is a requirement for modern intellects. Right now, a lot of those intellects are already testing intelligent applications that could cause entire vertical industries to converge in the most unexpected of ways. It’s the job of the IT leadership in 2017 to make certain that their organization is on the giving rather than receiving end of those unexpected digital transformations.

MV

Michael Vizard is a seasoned IT journalist, with nearly 30 years of experience writing and editing about enterprise IT issues. He is a contributor to publications including Programmableweb, IT Business Edge, CIOinsight and UBM Tech. He formerly was editorial director for Ziff-Davis Enterprise, where he launched the company’s custom content division, and has also served as editor in chief for CRN and InfoWorld. He also has held editorial positions at PC Week, Computerworld and Digital Review.

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