AI as Critical Infrastructure

The United States does not have the luxury of sitting out the development of advanced artificial intelligence. Capability will be built somewhere. The question is whether democratic societies will lead — and whether they will build the governance mechanisms to ensure that leadership serves the public interest.

Treating AI as critical infrastructure means applying the same policy logic we apply to electricity grids, water systems, and interstate highways: that certain capabilities are too important to leave entirely to private actors operating without public accountability. It does not mean nationalization. It means sustained public investment, antitrust vigilance, interoperability requirements, and procurement reform.

The semiconductor supply chain is already recognized as a national security priority. The same logic applies to compute capacity, energy systems that power datacenters, and the talent pipeline that staffs AI labs. These are not private luxuries. They are strategic assets.

Democratic governance of AI infrastructure will require agencies that can actually understand what they are regulating. That means technical fellowship programs, embedded expertise, and procurement pathways that let government adopt proven tools without locking into a single vendor. It is unglamorous work. It is the work that matters.