Applications of Cognitive technologies


Where do we see automation, machine learning and cognitive technologies seep into our lives. From a traditional categorization perspective there is the well know business to consumer (B2C) and business to business (B2B).

For the B2C segment, there is increasing intensity on customer behaviour prediction, customer service, ordering and search and recommendation technologies that are gaining prevalence. eCommerce is a heavy user of search and recommendation technologies, self driving cars and image recognition is another consumer product that promises to change the world of transportation. The prevalence of No-SQL data technologies and schematic search has opened up avenues and activities to analyze massive amounts of consumer data and preferences, companies like Google, Facebook, Netflix and Amazon are investing massive resources to understand the consumer and feed them a constant stream of content and product recommendations.

The approach and direction gets more interesting in B2B segments where the intent is insights and optimizations into business processes. In the traditional prism of viewing business processes as a layered structure of Tools Tech at the bottom, process in the middle and people at the top, the People layer represents an interesting use case.

An inordinate amount of spend will be focused towards the marketing and sales segment that drives organizational growth. The other optimizing angle is the world of employee engagement and HR analytics. A interesting use case also exists in the candidate and recruitment life cycle where insights can be gleaned from massive resume databases like LinkedIn and others. The age of a people platform driven by new age machine learning technologies will be upon us soon. The ability to detect sentiment, the pervasiveness of social media networks, creation of standardized behavioral measurement frameworks could soon provide us the ability to predict people on actions and capabilities.

Such prediction technologies will be much more useful on the customer and candidate side of the people chain where none to minimal is known about the individual and any conclusions based on analyzing publicly available data will provide objective decision support over gut and experience based traditional approaches.

By Deepak Nachnani