TL;DRThe assumption that the biggest AI model wins is breaking down, with enterprises now choosing models by task, cost, and control rather than leaderboard rank. Driving it are model bills running to millions a month, the rise of model routing, and specialised task-specific agents, which Gartner expects in 40% of enterprise applications by end-2026, up from under 5%. If capability is commoditising, the margin moves to whoever runs inference cheapest.
For years the industry ran on one assumption, that the biggest model wins. That belief is now breaking down, CNBC reports.
Companies are choosing models by task, cost, and control instead of benchmark position. The frontier still matters, but it is no longer the only thing being bought.
The reason is unromantic. At enterprise scale, model bills run into millions of dollars a month.
The rise of good enough
