Securing Infrastructure Before You Need It
Negotiate compute when leverage is real — before inference costs compound indefinitely.
The Economic Case
The true cost of AI in government is not model development — it's inference. A model trained once can serve a city for decades, but every query to a commercial API compounds that dependency indefinitely. By negotiating compute set-asides during data center permitting — while municipalities hold rare leverage over power-hungry facilities — cities can lock in the infrastructure they'll need before the models are even built.
The sequencing matters: secure the compute now, develop the models on whatever timeline funding allows, and deploy into an infrastructure commitment already in place. The marginal cost of inference is locked in at the moment of greatest negotiating power.
What to Ask For in the Next Permit
Municipalities currently negotiate traffic studies, affordable housing set-asides, and stormwater infrastructure as permit conditions. Compute access is no different in principle.
"As a condition of approval, Applicant shall reserve not less than [X]% of total GPU compute capacity — or an equivalent allocation of [Y] GPU-hours per month — for use by [Municipality] for public-interest AI workloads. This allocation shall be subject to an SLA guaranteeing [Z]% uptime, shall survive any change of operator or ownership of the facility, and shall be transferable to a successor public entity. Specific workload types, access protocols, and performance standards shall be defined in a Compute Access Agreement to be executed prior to certificate of occupancy."
This is a starting point for negotiation, not legal advice. A city attorney should adapt it to local permitting law.
The Cost You're Not Counting
The true long-term cost of commercial AI is not the contract or the integration — it's every inference call, forever. Frame this as a present-value problem: a municipality that secures compute access now, when leverage is highest, is hedging decades of operational cost at today's negotiating position.