Why did the finance teams who called themselves most mature at AI cost control do worse than everyone else?

If Technology says it owns AI cost 55% of the time and Finance says 53%, who actually owns it?

Why does 40 to 60% of what an AI feature actually costs never show up on the vendor invoice?

AI spend stopped being an engineering experiment and became a real line on your budget, and in most buildings nobody, not Technology and not the CFO’s office, actually owns it. Nobody owns the number. In this episode, I break down why your pilot number was never going to survive production, the mechanical reason AI cost grows like a triangle instead of a line, and the three levers, ones you already know how to pull, that bring it back down.

• FinOps Foundation, State of FinOps 2026 and the Token Economics guidance
• Deloitte CFO Signals Q2 2026 (200 CFOs at $1B+ companies)
• DoiT and Sapio Research AI spending survey (500 finance leaders)
• Flexera 2026 State of ITAM (512 IT asset managers)
• Datadog State of AI Engineering 2026
• Anthropic prompt caching and batch pricing documentation
• Finance AI Insider, the free weekly newsletter: https://www.f9finance.com/newsletter/

This episode’s sponsor is Finance AI Lab. Members who finish their first four roadmaps get about seven hours a week back. Fifty-nine dollars a month, cancel anytime. https://www.f9finance.com/lab/

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• Resources -> https://www.f9finance.com/ai-library/

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Excel at AI in Finance is for the finance pro who wants AI to actually hold up under a CFO’s scrutiny, not just look good in a demo. Mike is a senior finance leader breaking down AI tools used in FP&A, reporting, and automation, to cut hours and avoid burnout.