2026 will be remembered as the year pharma went all in on AI.

Since January, nearly every major pharmaceutical company has announced some version of the same thing. GSK signed a five-year foundation-model deal with Noetik. Eli Lilly built a co-innovation lab with NVIDIA. Merck committed a billion dollars to Google Cloud. This month, Novo Nordisk named Amazon Web Services its preferred AI partner. The dollar figures are staggering. And the messaging has been almost identical across all of them: get access to the right model, the right compute, the right discovery platform, and you’ll win the next decade of drug development.

Then Q2 earnings calls wrapped, and almost no one could point to a measurable return. A faster trial. A failure caught earlier. A drug that reached folks sooner because of what they’d invested. Executives talked about pilots and roadmaps. The announcements are loud but the silence on results is the real story.

I get why these deals get announced the way they do. The models are really incredible. But when everyone has access to roughly the same model capability, the model stops being an advantage. It becomes table stakes, like electricity. Nobody wins on having electricity. They win on what they build with it.

A lot of the conversation this year has moved toward the discovery platform or the algorithm on top of the model as the real differentiator. That’s closer. But I’d push it one level further. The real edge is the data the platform is trained and run on.

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