Business media runs a steady stream of case studies about companies that adopted an AI tool and benefited from it. What's almost entirely absent is the mirror image: companies that seriously evaluated an AI vendor, ran the numbers, and correctly decided not to buy - because the fit was wrong, the cost didn't clear the bar, or an existing process was already good enough.
Why this story doesn't get written
A vendor has every incentive to publicize a customer win and none to publicize a lost deal. A company that declined to buy has little incentive to talk about it publicly either - there's no press release template for "we looked at this and passed." The result is a media record that only captures one side of every purchasing decision.
Why the missing half matters
A business trying to calibrate its own AI evaluation process has no public benchmark for what a good "no" looks like, only examples of what a good "yes" looks like. That's a real gap, because the discipline to walk away from a bad fit is arguably a harder and more valuable skill than the willingness to adopt.
What a good declined-deal story would include
The specific criteria that weren't met, the actual numbers that didn't pencil out, and what the company did instead - whether that was sticking with an existing process, building something narrower in-house, or waiting for the technology to mature. These specifics are exactly what makes an adoption case study useful, and they're just as available on the other side of a decision.
An invitation
If your company evaluated an AI vendor and passed, that's a more useful story to us than another success story, and one we'd genuinely like to hear.