Most AI integrations stop at chat. Chat with a bot. Chat with a PDF. Chat with a bot that chats with other bots. It’s everywhere—and mostly unhelpful.

Some time ago, my wife and I were planning a trip to France and Italy for our family (mostly my wife because she’s just awesome), and I was doing the DevOps Director thing, blissfully unaware of the impactful changes that AI would soon have on my emotional state, my existential complacency, and my hope for an abundant future.

AI can be transformative, but it can also fail spectacularly if user experience and real-world needs aren’t top priorities. Sometimes, the biggest danger is what you don’t see: overconfidence in AI’s novelty, untested assumptions, and a fuzzy plan for how users will adapt. Below, we’ll explore the six biggest ways AI projects go off the rails, along with strategies to mitigate risk and apply a rigorous process to your next AI initiative.