Most organizations can see their AI bill. Fewer can say what it buys. AI providers charge by token, the unit each request consumes, and that spend grows with usage across teams, tools and projects. The unit price is rarely the real problem. The problem is that most leaders cannot say which team, project or product drives the spend until the invoice arrives. By then the cost is already locked in, and nobody has a clear lever to pull.

Waiting for the invoice creates a second problem. Cutting spend without knowing where it goes means cutting blind. Teams slow down, the wrong workloads lose capacity, and the savings rarely last. Leaders end up asking the same question each quarter: what did we get for this?

This webinar answers that question in order. We start with visibility: where AI spend goes, by project, user and provider. Next comes control, meaning limits that reflect business priorities rather than a blanket cap. Then optimization: sending each task to the model that suits it, instead of defaulting to the most expensive one. Last, we connect the spend to operational improvements you can measure, so the discussion ends on value and not on the bill.

Enouvo presents a use case from its own engineering work, including how a central AI gateway gives traceability over every model call. A panel of leaders from different sectors then explains how they run AI in their own organizations, where they found the spend, and what they changed. The session closes with Q&A, live or in chat, so you can test the approach against your own situation.

This session is for business leaders who are responsible for AI budgets, operations or delivery outcomes, and who need to control cost without slowing the people using AI.