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Cheap AI Output Can Still Be Expensive Work. Here’s How to Tell.

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Cheap AI Output Can Still Be Expensive Work. Here’s How to Tell.

Most owners buy AI for speed and discover the checking cost later. A competent person can verify the output cheaply and still say no.

The first time I watched a machine draft something that looked finished, I almost signed off. The language was clean. The structure made sense. Then I tried to check three claims against the source material and burned more time reconstructing the case than the draft had saved. Speed had moved. The cost had not gone away. It had just changed rooms.

I remember the annoyance more than the draft. The tool had done its job. The review path had not.

Here’s my situation, so you know where I’m coming from. I founded Main & Machine, an AI implementation firm for small and mid-size businesses, and I also sit in the buyer seat when technology lands in a real operating company. (Disclosure for the editor: I have a financial relationship with Main & Machine.) I teach management and entrepreneurship at Arizona State University’s W.P. Carey School of Business. Across those chairs I keep seeing the same pattern: owners celebrate generation and underbuild verification.

Most shops treat “human in the loop” as a checkbox on a vendor slide. That move fails in practice. The economic value of generated output depends on how cheaply and reliably a competent person can verify it in the real decision. S. Census Bureau data from late 2025 through early 2026 put overall business AI use in the 17% to 20% range, with more firms still planning to join them.


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