In the data science world, everything's a technical problem and we solve it with tech. But I fully believe that a lot of the reason this stuff isn't going into the business processes is basically a cultural, political, or people problem - not a technical problem.
Business executives must understand AI to champion and achieve project success. Executives learn better through use case examples rather than 'data science 101' courses.
The failure of AI projects can often be caused by business stakeholders not trusting the AI model's results because they weren't part of the process.
As long as the data is there, Hillman's team can successfully train, test, and evaluate AI models. We write the output of that model somewhere, and that's job done.
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