I have often discussed the topic of taking AI models (actually, all analytical models) out of the one-off, Proof-of-Concept concept into a scalable, engineering paradigm. Needless to say, this topic is not new – most organizations are struggling with this. Which begs the question: why is it so hard to scale these systems? Could be... Continue Reading →

Had a very good discussion on this topic at the AI Innovation Summit last week (full slide deck here). Here's the synopsis: Hype or Reality: Take the 10 Questions It is tempting to look for a cut-off score to be able to declare that AI in your enterprise is 'real'. And the right answer is... Continue Reading →

I am speaking at the AI Innovation Summit in San Fransisco later this month (https://analyticsevent.com/) on this topic. Here is the outline of what I am planning to cover. Would be great to have your feedback - nothing like crowdsourcing! AI in the Enterprise Step out of the giddy enthusiasm about all things AI in... Continue Reading →

Management jargon like ‘Extreme Experimentation’, ‘Fail Fast’ have been around for some time now. Much of this thinking and consequently, success has come from the software industry. But once you step outside the Silicon Valley, you will find hard pressed to find successful instances of experimentation translating to actual shareholder value. In my years of... Continue Reading →

In my role as Head of Data Science and Analytics, the single most important problem that I am trying to solve is: What does a world-class team look like? How should you build and more importantly, sustain such a team? It is always best to start with a few basic axioms (I call them so... Continue Reading →