Companies are not struggling to adopt AI anymore. They are struggling to explain the bill.

AI usage has moved from experiment to operating line item. The next problem is not whether teams can use AI, but whether leaders can explain which agents, workflows, API keys, and teams are driving the spend.

The AI cost conversation has changed. For the last two years, the question was adoption: which teams are using AI, which models are good enough, and where can agents remove manual work?

Now the question is operational: why did this workflow cost what it cost, who owns it, and what changed before the spike?

You can see it in the headlines. Axios reported comments from Nvidia's VP of applied deep learning arguing that compute costs can move beyond employee costs. TechCrunch reported that Uber had to cap employee AI tool spending after usage ran far ahead of plan. Derek Thompson also highlighted Ramp data showing business AI token spend rising sharply since early 2025.

Provider dashboards show the bill. They do not explain the workflow.

A provider dashboard can tell a team that model usage went up. That is useful, but it is not enough for an enterprise operator, product leader, or finance owner.

They need answers like:

• Which agent caused the spike?
• Which API key, team, or owner was responsible?
• Was it a loop, retry cascade, model mismatch, or normal growth?
• Which exact request window created the exposure?
• What fix would reduce the risk without blocking useful work?

The next layer is diagnostic infrastructure.

AI cost control should not only be a budget number. Budgets tell you when something is too expensive. Diagnostics tell you why it happened and where to intervene.

That is the layer Costile is building: an AI agent diagnostic proxy that connects spend to agents, sessions, API keys, teams, owners, and incident windows. The goal is to make AI cost explainable enough that teams can fix the cause instead of arguing over the invoice.

The better question is not "how much did AI cost?"

It is: which workflow changed, who owns it, what evidence proves the cause, and what should we do next?

Your agents are burning money. Costile shows you why.