We had a large piece of work that was funded partially by the fact that it “introduced machine learning”. So we did what I always do; start with the introduction of an evaluation system; the goal being to baseline the incumbent deterministic business rules. Just doing the evaluation meant that we discovered some problems with upstream data which meant we could improve things overall just by a data processing change. This was enough to actually move onto something else for a bit. When we came back to it later the next thing was to improve the business rules, still without introducing anything anyone would call ML. I’ll never forget after that release a key exec stakeholder pulling me aside and asked “are we doing machine learning yet?”. It always makes me laugh. So much hype that for them the key result wasn’t a better user outcome, it was whether we were “using machine learning”