AI-scale data centers are changing the economic development bargain. As power, land, water, permitting and speed-to-market become scarce, governments are gaining leverage to demand tougher terms, greater public benefits and fewer subsidies.
Municipal governments do not need to match AI vendors alone. By connecting existing professional networks, sharing lessons faster, and building a stronger vendor feedback loop, they can gain scale without giving up local authority.
The most important pattern this week is the simultaneous movement in opposite directions. Government is becoming a more consequential gatekeeper over frontier-model release and hyperscale infrastructure, while open weights and on-device models are making technical alternatives more plausible—and the portability question is becoming more concrete. * White House
As AI systems learn our preferences, projects, and workflows, portability will determine whether model choice becomes customer power.
The federal government is becoming the gatekeeper for a privately owned AI infrastructure system. That combination concentrates power—and creates structural incentives for corruption.
This week's note starts with the monthly update for July - where we try to gather up all the events we've studied during the month and tell you where we think things stand. The result - there's still a bias of activity toward centralization, but the
AI is not simply replacing jobs. It is compressing teams, shifting work outside firms, concentrating implementation expertise, and changing who holds authority. The early workforce struggle is over who controls the redesign—and whether workers can contest it.
Six practical questions help reveal whether AI choices can still be changed. Applied to data centers, Android, OpenAI Presence, and Meta’s Hyperion project, they show a window being preserved, reopened, narrowed—and nearly closed.
AI data centers are no longer merely local land-use projects. They are claims on regional power, water, infrastructure, and public capacity. Can our distributed institutions govern the whole before the choices become difficult to reverse?
I have spent the last several weeks reorganizing and restructuring the website of The Race. The major change is rather than try to reduce coverage to a single stream, we're now tracking activity across eight 'lanes'. Activity in AI adoption is happening in so many places
AI will not reshape society through algorithms alone. It will depend on whether governments, schools, utilities, and other public institutions develop the capacity to understand, procure, and govern it before dependence on a handful of private actors becomes the default.
AI’s physical expansion depends on electricity, water, land, and grid access. That gives utilities, regulators, and local governments a crucial opening to shape who pays, who benefits, and whether the public retains a meaningful say in the AI race.
States are beginning to build a public layer for AI through inventories, procurement rules, training, shared tools, and limits on consequential uses. The framework is emerging, but dependence on private platforms remains its weakest point.
Buying access to AI is easy. Durable implementation capacity depends on whether organizations can redesign workflows, train people, preserve learning, and switch providers without surrendering control to vendors or platforms.
Governments are beginning to decide who can access frontier AI, under what safeguards, and through which trusted-user systems. The challenge is to address real security risks without turning advanced capability into permanent discretionary privilege.
Public models and public compute are only the beginning. AI becomes public infrastructure when governments and civic institutions can use, adapt, govern, and sustain it without becoming permanently dependent on a single vendor.
AI assistants may begin as convenient doorways into information and services, then become the operating layer that shapes what users see, choose, and do. The challenge is to preserve that convenience while keeping the path open, portable, and contestable.
AI may be overhyped in the short run and underestimated in the long run. The lag before its benefits spread is also a concentration window, when infrastructure, defaults, and dependencies may harden around a few powerful actors.
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This is The Race: Building Democracy in the Age of AI, a brand new site by Mark Howard that's just getting started. Things will be up and running here shortly, but you can subscribe in the meantime if you'd like to stay up to date and