By now, it’s clear that the only way the tech industry can justify the cost of AI is if it replaces vast swaths of the human workforce with machines that run 24/7.

The bad news is that this situation has created a world-historic financial market that, by some metrics, is looking worse than the run-up to the Great Depression. The good news is that this future of an AI takeover is looking increasingly unlikely, at least at the industry’s current pace, a fact which is now dawning on some of the biggest rubes and dupes in the corporate world.

According to a new survey from “Big Four” accounting firm KPMG, a significant number of corporate executives are reeling from sticker shock over new usage-based AI pricing schemes. Though enterprises could once count on AI companies to subsidize the price of large language models via flat-rate contracts, that’s no longer a given, as the rising cost of computational power forces the entire tech sector into a defensive posture.

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“As usage-based pricing models become more common, many organizations are still building the capabilities required to forecast, monitor, and manage AI spending effectively,” the report authors write. Translation: one third of execs had no plan for how to actually use AI productively, a fact which is becoming increasingly clear now that the meter is running.

The finding underscores what many workers forced to use AI tools on the job have come to suspect: that an alarming number of corporate leaders treat AI as a plug-and-play solution for lowering overheard without understanding the how of it all, a kind of magical thinking entirely divorced from practical reality.

On the same token, it’s important not to lose sight of the fact that AI — or more accurately, the myth surrounding it — is currently being deployed across the world as a tool to discipline labor, to force workers into a weaker position when it comes to wage negotiations, benefits, and overall stability.

Whether used as an excuse to strap surveillance cameras to factory workers’ heads or as a justification for widespread layoffs, execs don’t need to a PhD in machine learning to know that AI in its current, error-prone form is mainly good for keeping the worker bees in line.