The High Cost of Cheap AI: A Cheatsheet to the Hidden Patterns Behind AI Disasters

Eight lessons we can learn from the real failures—and costly fallout—of rushed AI deployments, plus a full set of takeaways for AI teams who want to avoid the next Air Canada chatbot disaster.

We hear too many happy path AI stories these days. So here’s a post about some prominent AI disasters. I’m particularly interested in uncovering the hidden patterns behind these very public screwups, because I think we can learn from them as AI builders. Happy reading and remember—next time it could be you (or me!)

We begin with nuggies…

On a scorching summer day, a driver in a crowded McDonald’s drive-thru calmly requested a 10-piece Chicken McNuggets meal. The AI-powered ordering system seemed polite at first, but then—unprompted—it added more nuggets to the order. And more. And more. By the time the customer’s pleas of “Stop!” were ignored for the umpteenth time, the order had ballooned to 260 nuggets. It was an amusing catastrophe—for outsiders. Within three months, McDonald’s scrapped the entire AI project, prematurely ending a three-year partnership with IBM. Millions of dollars of investment went up in smoke.

This might sound like a one-off fiasco—just another AI blooper destined to become a social media meme. But it’s not. Beneath the comedic surface lurks a pattern we see repeated across industries, product types, and organizational cultures. From fast food to real estate, from finance to healthcare, costly AI failures are more common than we’d like to admit. While each disaster appears unique, they often share a common cause: an unchecked desire to cut corners that leads to hidden “gotchas” piling up behind the scenes.

The irony? Nearly every failed AI project started with good intentions and “reasonable” compromises. Taken in isolation, none seemed egregious. But AI systems magnify small flaws, allowing them to grow into epic, brand-tarnishing, and sometimes user-endangering blowups. This article aims to tease out these hidden patterns so that—unlike the McDonald’s AI that couldn’t resist a good nugget—you can learn to say “Stop!” before it’s too late.