California's AI data centre bill ends up studying the problem, not fixing it

California has spent much of the past year positioning itself as the state most willing to put guardrails on artificial intelligence, from model-safety disclosure rules to fights with the federal government over pre-emption. So it is notable that its answer to one of the most concrete AI harms now landing on households — the electricity costs of a data centre boom concentrated in a handful of grid regions — is not a rule at all. The law that survived Sacramento’s session, Senate Bill 57, directs the California Public Utilities Commission to study and identify ways to mitigate data centres’ impact on ratepayers, rather than cap costs, tax operators, or force disclosure of what they draw from the grid.

That outcome was not an accident of drafting. Earlier versions of the bill would have required the Commission to set a special tariff protecting other ratepayers from the transmission costs of large new loads, making data centre operators bear more of the infrastructure costs they generate; those provisions were stripped out before the bill became law, leaving a commitment to gather data rather than a binding formula. The industry’s case for that outcome is not purely self-interested: cost-allocation rules written before regulators know how much new demand will actually materialise, or how much of it will bring its own generation, risk locking in numbers that turn out to be wrong, and several state utility commissions already handle large-load costs through bespoke tariffs negotiated case by case rather than blanket statute. But that same argument for caution has, in practice, produced study after study while data centres are financed, sited and built well ahead of any enforceable cost-sharing rule.

A state that can pass an AI safety law can apparently still be talked out of an AI utility bill.

The pattern is becoming familiar beyond California. Grid operators and state regulators elsewhere have leaned on negotiation rather than mandate to decide how much of the cost of new data centre demand gets socialised across ordinary ratepayers, and the industry’s preferred outcome is consistently the same: more time, more studies, fewer binding numbers before the infrastructure is already built and the political cost of unwinding it has risen. California’s experience suggests that even in the state most inclined to regulate AI on principle, the industry’s leverage over its physical footprint — the power plants, substations and transmission lines it actually needs — remains stronger than its leverage over the software itself.