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Gartner’s India Hype Cycle: ML Among to Have Business Impact Within Two to Five Years

The 2018 Gartner, Inc. Hype Cycle for information and communication technology (ICT) in India classifies machine learning (ML) among three technologies that will have a transformational business impact within the next two to five years

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The 2018 Gartner, Inc. Hype Cycle for information and communication technology (ICT) in India classifies machine learning (ML) among three technologies that will have a transformational business impact within the next two to five years.

The ICT Hype Cycle identifies 28 key technologies and capabilities for digital transformation that are important for local Indian IT leaders (see Figure 1). The focus is on three stages of digital business delivery — designing, delivering and scaling — which reflect the focus of 75 percent of CIOs in India.

“Scaling business is the primary objective of Indian CIOs,”said Pankaj Prasad, principal research analyst at Gartner. “Doing it right requires continued investment in proven technologies and balanced investment in emerging technologies that sustain growth.”

Gartner analysts classified 13 technologies on the Hype Cycle that will take two to five years to reach mainstream adoption. Of these 13, the three technologies that will have transformational impact on organizations are machine learning, edge computing and platform as a service (PaaS).

Machine learning continues to climb up the hype curve in India. ML has moved from being at the Innovation Trigger in 2017 to close to the Peak on this year’s Hype Cycle.

Organizations in India, across various industries, are still evaluating ML and experimenting with it. “There is a lack of understanding of the technology and therefore user adoption is currently limited,” said Mr. Prasad. While large banks and insurance companies in India are either evaluating or piloting specific use cases (for example, fraud prediction, lending appraisal and propensity to buy prediction), organizations in retail are evaluating and piloting ML concepts in customer segmentation, churn analysis and predictive modeling of buying behavior. “In the healthcare and pharmaceutical sector, we witness some use cases particularly in drug research and oncology/cancer research,” he added.

Edge computing made its entry onto the Hype Cycle this year and moved to the Peak of Inflated Expectations. Gartner defines edge computing as solutions that facilitate data processing at or near the source of data generation. For example, in the context of the Internet of Things, the sources of data generation are usually things with sensors or embedded devices.

Edge computing serves as the decentralized extension of the campus networks, cellular networks, data center networks or the cloud. It solves many issues as it decreases latency and reduces unnecessary traffic. It also establishes a hub for interconnection between interested peers and a hub for data thinning of complex media types or computational loads.


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