OpenAI CFO Sarah Friar is pitching a new enterprise AI metric called "useful intelligence per dollar" in response to a growing cost reckoning, as companies demand clearer returns on their investments. Instead of measuring AI spend by expenses or cost per token, Friar argues businesses should ask four questions: whether AI completes work that matters, what each successful task costs, how often it gets the work right, and whether each AI dollar produces more value as usage grows. OpenAI is trying to shift the conversation from the price of AI to the value it creates. CFOs are widely flying blind on AI costs; one executive oversaw a half a billion dollar accidental Claude bill over the course of one month. OpenAI CEO Sam Altman said costs are the second biggest challenge customers discuss with him. Friar writes that the basic economic question is whether the value of the work AI completes grows faster than the cost of producing it. However, many enterprises are responding differently than OpenAI might like, increasingly routing everyday tasks to the cheapest model that can do the job and using frontier AI models only for the most intensive tasks.