“AI pilots” in the article refers to developing AI-based tools, not to using AI for software development. These projects have a 95% failure rate of successfully deploying the AI tool being developed into production.

Regarding use of AI in software development (which is not what the article is about), the proof of the pudding isn’t in greenfield projects, it’s in longer-term software evolution and legacy code. Few disagree that AI saves time for prototyping or creating a first MVP.

You are correct. As I pointed out in another reply, I misinterpreted this part:

> Generic tools like ChatGPT excel for individuals because of their flexibility, but they stall in enterprise use since they don’t learn from or adapt to workflows, Challapally explained.

I didn't read the actual report (and probably wont) so I was figured "AI Pilots" _could_ (and honestly, should!) include the deployment of models to assist in any and all work (not necessarily even just coding - I just used it as an example).