AI projects are exciting, but they rarely go the way the demo videos suggest. In real life, you run into messy data, models that behave unpredictably, costs that climb faster than expected, or governance rules that slow everything down.
I’ll share some of the good, bad, and ugly lessons I’ve learned while working on AI solutions in enterprise environments: what actually works, what usually causes trouble, and the kind of mistakes you only make once. In summary, a mix of practical tips, real stories, and lessons learned that will help you set up your own AI projects for success.