Today's episode is part four out of five in our Achieving ROI with Early AI Projects series. This week, we have published one episode per day, starting with the Head of the AI Centre of Excellence for Intel. Today, we're bringing it down to more of a consultancy and vendor perspective from someone who has worked with some of the largest enterprises in the world. Our guest is Dr. Charles Martin, a Silicon Valley AI Consultant with hands-on machine learning experience with organizations like Ebay, BlackRock, and more. In this episode, Charles discusses the concept of data quality mismatch, which can serve as a useful diagnostic tool for estimating what kinds of tasks it will be best suited for. He also speaks about picking projects where you have the data assets to achieve ROI. Be sure to visit emerj.com/p1 to access Emerj's frameworks for AI readiness, ROI, and strategy.

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“What did the council decide on item 42?” — answered with the speaker and the moment.

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