AI overspend is a misallocation problem, not a pricing problem

Companies are not overpaying for AI. They are paying frontier prices for tasks a small model could handle for cents. That distinction is the whole story: a pricing problem invites a vendor negotiation, a misallocation problem asks you to rewrite the workflow.

Manos Koukoumidis at Oumi AI, whose $10 million seed round in 2024 made the bet explicit, called routing niche work through OpenAI, Anthropic, and Google "widely irrational and inefficient." Capital following him is the part Business Insider's catalog framing misses: the build layer, made up of model makers and inference platforms that attack cost at the source, is one where the savings are most structural. Oumi's Koukoumidis argues cheap inference is durable while renegotiated enterprise contracts are a tactical rather than structural fix.

Adaptovate partner Michael Murphy mapped the rest of the service layer into two more categories. Coaches redesign the workflow. Measurers instrument the spend. Each one answers a different question: how is the work actually done, where is the AI paying back, and what is the right model for this task. Buying one while the waste lives in another is how AI projects keep looking tidy in pilots and ugly on the invoice.

The fix is not to use less AI. It is to match the cost of the tool to the value of the job.