Paradox of Choice and Enterprise AI

Sam Taha
Sam Taha
Aug 28, 2017 · 1 min read

The paradox of choice is a problem we see more and more of in our modern world. It goes beyond what products Amazon should recommend or friends Facebook should suggest. In the business world and in enterprise applications this is also a challenging problem as our applications and processes grow in complexity. The potential for machine learning powered recommender systems to augment human decision making is one of the next frontier for AI in the enterprise .

Recommender systems can do more than just suggest what articles you should read on Linkedin or what jobs are most suited for you. In the future machine learning (and more likely deep learning) powered recommender systems will guide enterprise decision making by helping business process owners take the most effective actions and decisions in a timely manner and with hyper-personalization.

Recommender systems will move from solving B2C optimization challenges, like they do today in our data saturated and over marketed world, to solving problems in B2B and enterprise applications. Ultimately recommender systems are are about prescribing an optimal decision at the right time and place/context, and enterprise decision makers will be in vital of these AI super powers :)


Originally published at grandlogic.blogspot.com on August 28, 2017.

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