95% of generative AI pilots at companies are failing – MIT report

> Despite the rush to integrate powerful new models, about 5% of AI pilot programs achieve rapid revenue acceleration; the vast majority stall, delivering little to no measurable impact on P&L.

This summer, I built two very sophisticated pieces of software. A financial ledger to power accrual accounting operations and a code generation framework that scaffolds a database from a defined data model to the frontend components and everything in between.

I used ChatGPT substantially. I'm not sure how long it would have taken without generative AI, but in reality, I would have just given up out of frustration or exhaustion. From the outside, it would appear to any domain expert that at least three other people worked on these giving the pace at which they got completed.

The completion of those two were seminal moments for me. I can't imagine how anyone, in any field of information systems, is not multiples more effective than they were five years ago. That directly affects a P&L and I can't think of anything in my career that is even remotely close to having that magnitude.

I don't know what encapsulates an AI pilot in these orgs, and I'm sure they are massively more complex than anything I've done. But to hear 95% of these efforts don't have a demonstrable effect is just wild.

No. I also thought that even a 95% success rate wouldn't be good enough for airplanes.

Any consumer facing AI project has to contend with the fact that GenAI is predominantly associated with "slop." If you're not actively using an AI tool, most of your experience with GenAI is seeing social media or Youtube flooded with low quality AI content, or having to deal with useless AI customer support. This gives the impression that AI is just cheap garbage, and something that should be actively avoided.

short nvidia?