Perspective · 3 min read
The next era of enterprise spend is measured in tokens
Infrastructure, licensing, cloud — every era of IT had its cost unit. The AI era's unit is the token, and most enterprises cannot account for it.
A new cost discipline
Enterprise technology spend has always followed its unit of consumption: servers, then licenses, then cloud instance-hours. AI introduces a stranger unit — the token — and with it a cost structure that scales with every conversation, every context window, every agent action. An assistant that delights ten users can bankrupt its business case at ten thousand. Agentic systems multiply this: a single request can fan out into thousands of model calls across chained tools.
AI FinOps
The organizations that scale AI sustainably treat token economics the way mature engineering organizations treat cloud cost: as a first-class discipline. That means visibility per use case, budgets per capability, unit economics per outcome — cost per resolved ticket, per validated document, per decision supported — and the authority to redesign or retire what doesn't earn its consumption. We call this AI FinOps, and within it the questions become answerable: What does this capability cost? What does it return? Should it run on a frontier model or a distilled one?
Value you can defend
Boards no longer ask whether the organization uses AI. They ask what it returns. Token-level economics is how that question gets an honest answer — and honest answers are what let AI budgets survive their third year.