Effective AI governance starts with an "AI Council" composed of passionate users, IT, legal, and operations staff. Unlike a top-down "Center of Excellence" that dictates rules, this council's primary role is to create enabling policies and guidelines that empower grassroots adoption and safe experimentation across the organization.

The national political conversation on AI isn't led by D.C. think tanks but by local communities protesting the impact of data centers on electricity prices and resources. This organic, grassroots opposition means national politicians are playing catch-up to voter sentiment.

To overcome local opposition, tech giants should use their massive balance sheets to provide tangible economic benefits to host communities. Subsidizing local electricity bills or funding renewable energy projects can turn residents into supporters, clearing the path for essential AI infrastructure development.

The most successful companies deploying AI use a "leadership lab and crowd" model. Leadership provides clear direction, while the entire organization is given access to tools to experiment and discover novel use cases. An internal team then harvests these grassroots ideas for strategic implementation.

Public distrust of AI arises because the technology feels remote and disconnected from daily life. SeedAI argues that giving communities genuine agency and avenues for participation—making AI relevant to them—is more effective at building trust than simply explaining the technology's benefits.

Before ChatGPT, SeedAI had to convince communities of AI's importance. After its release, communities urgently sought their guidance, dramatically shifting the nonprofit's operational focus from outbound education to handling a flood of inbound requests for strategic planning.

OpenAI is shifting its policy strategy, now supporting state-level regulations like those in Illinois. This marks a move away from waiting for a comprehensive federal standard towards a more practical approach that acknowledges public sentiment and the need to build trust locally.

To counter local opposition to data centers, Brad Gerstner proposes a "community dividend." This initiative, involving tech leaders and the White House, would provide tangible financial benefits to host communities, creating a socio-political bridge until AI's broader advantages are obvious.

National AI strategies are vulnerable to local politics. Community backlash over data centers' strain on power grids, water, and local costs is creating a "legitimacy constraint," making the ability to build politically durable infrastructure as crucial as acquiring chips.