India, Sept. 3 -- The most consequential change in enterprise AI this year is not a model release, it is a change in what buyers agree to pay for. OpenAI's CFO has recast the buyer's question away from cost per token and towards cost per successful task, proposing "useful intelligence per dollar" as the scorecard and arguing that AI should be measured by work accomplished rather than usage. By August 2026, the same leadership was telling investors that the age of "tokenmaxxing" had passed, as enterprises routed routine work to the cheapest capable model and reserved frontier models for the tasks that justified them.

The deeper reason this shift was inevitable is that effort and value were never tightly coupled. Industry observers buildin...