How to Respond to the Coming AI Cost Shock
About This Episode
Harvard Business Review published a piece by Stacia Garr on August 17, 2026 arguing that today's AI adoption was fueled by heavily subsidized pricing from enterprise software vendors, that the era is ending, and that companies are shifting toward usage-based charges. Vendors have been quietly absorbing the cost of GPUs, inference and tokens to acquire customers; as that subsidy is withdrawn, AI stops being a software line item and becomes a variable consumption cost that has to be budgeted, attributed and governed.
Our Take
The meter is not the bad news: it is the first honest price signal AI has ever had, since the subsidy hid a physical electricity-and-silicon cost behind a software price; the real danger is that companies cap the token bill, the one number that is easy to measure, and quietly buy worse work.
Continue Reading on Unscarcity
Compute Landlords: When AI Builders Become Rentiers
The article's core framework - that the firms who spent hundreds of billions building AI infrastructure discovered a second business charging everyone else to use it - explains the cost shock as rent coming due after a customer-acquisition subsidy, not as a pricing accident.
Goodhart's Law: Why AI Metrics Always Backfire
The obvious corporate response to a metered bill is to target and cap token spend, which is precisely the move that turns a useful measure into a gamed target and buys cheaper work rather than better work.