How CIOs Can Govern AI Costs as Usage Scales

AI costs become difficult to control when usage-driven model, token, agent, infrastructure and data expenses scale faster than business value. The article explains why traditional cloud FinOps is insufficient and sets out a seven-part governance framework covering ownership, real-time visibility, model routing, agent limits, cost-per-outcome metrics, automated guardrails and scale forecasting. It also highlights hidden operational and data costs that pilots often miss. CIOs and CTOs should treat AI cost controls as part of platform design rather than a monthly reporting exercise.