Hello and welcome to Eye on AI…In this edition: DeepSeek drops another impressive model…China tells companies not to buy Nvidia chips…and OpenEvidence scores an impressive result on the medical licensing exam.
Hi, it’s Jeremy here, just back from a few weeks of much needed vacation. It was nice to be able to get a little distance and perspective on the AI news cycle. (Although I did make an appearance on Rana el Kaliouby’s “Pioneers of AI” podcast to discuss the launch of GPT-5. You can check that out here.)
Returning this week, the news has been all about investor fears we’re in an “AI bubble”—and that it is about to either pop or deflate. Nervous investors drove the shares of many publicly-traded tech companies linked to AI-related trades, such as Nvidia, CoreWeave, Microsoft, and Alphabet down significantly this week.
To me, one of the clearest signs that we are in a bubble—at least in terms of publicly-traded AI stocks—is the extent to which investors are actively looking for reasons to bail. Take the supposed rationale for this week’s sell-off, which were Altman’s comments that he thought there was an AI bubble in venture-backed, privately-held AI startups and that MIT report which found that 95% of AI pilots fail. Altman wasn’t talking about the public companies that stock market investors have in their portfolios, but traders didn’t care. They chose to only read the headlines and interpret Altman’s remarks broadly. As for that MIT report, the market chose to read it as an indictment of AI as a whole and head for the exits—even though that’s not exactly what the research said, as we’ll see in a moment.
I’m going to spend the rest of this essay on the MIT report because I think it is relevant for Eye on AI readers beyond its implications for investors. The report looked at what companies are actually trying to do with AI and why they may not be succeeding. Entitled The GenAI Divide: State of AI in Business 2025, the report was published by MIT Media Lab’s NANDA Initiative. (My Fortune colleague Sheryl Estrada was one of the first to cover the report’s findings. You can read her coverage here.)
NANDA is an acronym for “Networked-Agents and Decentralized AI” and it is a project designed to create new protocols and a new architecture for an internet full of autonomous AI agents. NANDA might have an incentive to suggest that current AI methods aren’t working—but that if companies created more agentic AI systems using the NANDA protocol, their problems would disappear. There’s no indication that NANDA did anything to skew its survey results or to frame them in a particular light, but it is always important to consider the source.
Ok, now let’s look at what the report actually says. It interviewed 150 executives, surveyed 350 employees, and looked at 300 individual AI projects. It found that 95% of AI pilot projects failed to deliver any discernible financial savings or uplift in profits. These findings are not actually all that different from what a lot of previous surveys have found—and those surveys had no negative impact on the stock market. Consulting firm Capgemini found in 2023 that 88% of AI pilots failed to reach production. (S&P Global found earlier this year that 42% of generative AI pilots were abandoned—which is still not great).
