Local opposition to data center construction, often driven by a small number of activists, is directly costing the AI industry tens of billions in potential revenue by canceling gigawatts of necessary power capacity. This local friction represents a major bottleneck to AI's growth.

The tech industry wrongly compares AI to software, which has near-zero marginal costs for new users. In reality, providing access to frontier AI models is a zero-sum game during compute crunches because of immense computational requirements. Servicing another user is expensive, leading to rationed access.

The 'Andy Warhol Coke' era, where everyone could access the best AI for a low price, is over. As inference costs for more powerful models rise, companies are introducing expensive tiered access. This will create significant inequality in who can use frontier AI, with implications for transparency and regulation.

Previously ignored, the unprecedented scale of new AI data centers is now sparking significant grassroots opposition. NIMBY movements in key hubs like Virginia are beginning to oppose these projects, creating a potential bottleneck for the physical infrastructure required to power the AI revolution.

The argument that AI will reduce inequality is flawed because democratizing access to tools doesn't democratize the economics. Technology markets naturally consolidate power and wealth, as seen with search engines and social networks. The financial benefits of AI are likely to concentrate at the top.

Venture capitalist Josh Wolfe highlights a growing risk to AI's expansion: local politics. With over 300 bills for moratoriums on data centers across 30 states, rising electricity costs are fueling a political backlash that threatens the physical infrastructure required for AI growth.

Contrary to the idea of AI for all, the most powerful models will likely be restricted to a few high-paying clients to prevent distillation and maximize revenue. This creates a future where competitive advantage is defined by exclusive AI access, potentially allowing large incumbents to crush smaller competitors.

Google, Microsoft, and Amazon have all recently canceled data center projects due to local resistance over rising electricity prices, water usage, and noise. This grassroots NIMBYism is an emerging, significant, and unforeseen obstacle to building the critical infrastructure required for AI's advancement.

The utopian vision of AI-driven abundance is shadowed by the practical reality of wealth concentration. A key challenge for society will be developing mechanisms to redistribute the immense value generated by AI so its benefits are shared broadly.