A company laid off employees to save money by replacing them with AI. The irony? The AI infrastructure ended up costing more than the payroll they cut. It has been shared widely as a cautionary tale about rushing into AI adoption without proper cost analysis.

The story highlights a blind spot: AI costs from compute, API usage, and ongoing maintenance can add up quickly. For some workloads, humans remain more cost-effective. Jumping to AI without modeling the full cost picture leads to surprises.

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