Definition
The FinOps Foundation extends its framework to AI workloads, where costs come from token-based APIs, GPU capacity, data platforms and the many tools around them. Spend can grow quickly and unpredictably as usage, agents and context sizes grow.
FinOps for AI brings the usual disciplines (tagging and allocation, budgets and alerts, unit economics, commitment planning) plus AI-specific levers such as model routing, caching, prompt size and choosing smaller models where they are good enough.