Every few weeks, another multibillion-dollar AI data center is announced. The numbers keep getting bigger. So do the grid demands, the water consumption, and the land footprints.
A tech giant celebrates a new milestone. A small town wonders what it just signed away.
That disconnect deserves far more urgency than the latest LLM benchmark or model release.
The United States has no choice but to lead in artificial intelligence. China is investing aggressively, treating the technology as a geopolitical imperative. AI will dictate military capability, scientific breakthroughs, and economic hegemony for the next half-century. Falling behind is a luxury we cannot afford.
Winning, however, requires more than chips and capital. It requires a domestic social contract.
The American public has accepted massive technological disruption before because progress eventually minted a ticket to the middle class. Railroads built towns. Automobile factories created generational wealth. The internet launched millions of micro-economies and entirely new career paths. Workers lost jobs along the way, but they could always see new doors opening.
AI feels different. Because it is different.
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The empires building it are scaling to multi-trillion-dollar valuations while requiring a fraction of the headcount of the industrial giants that came before them. Compounding that anxiety, the jobs AI threatens sit squarely in the middle-class professional tier. Software developers. Designers. Accountants. Corporate marketers. Legal analysts. These are people who spent decades believing that a specialized college degree was an absolute shield against automation.
That reality carries explosive political and social consequences.
I spend a significant amount of time in boardrooms advising directors on AI strategy. The conversation almost always centers on velocity. How fast can we deploy? How much productivity can we unlock? What market share can we capture?
Almost no one asks the foundational question:
How long will the public support this pace of change if they believe they are bearing the infrastructure costs while a handful of zip codes collect the rewards?
That question belongs on every board agenda today.
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The surrounding debate usually retreats to predictable ideological corners. One side argues the government should simply tax and redistribute the wealth AI creates. The other promises that breakthroughs in medicine and science will eventually lift all boats.
Neither answer addresses the psychological reality of the American worker. People rarely oppose technology because they dislike progress; they oppose it when they realize progress no longer includes them.
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Every extractive industry in history eventually had to learn this lesson. Oil companies learned it. Mining conglomerates learned it. Wind and solar developers are learning it now. Communities supplying the land, the electricity, the water, and the political baseline expect more than a corporate ribbon-cutting and a dozen permanent jobs.
AI infrastructure providers must anticipate the same reckoning.
When a tech company builds a data center designed to operate for decades, the host community should be able to point to an asset that will actually endure for generations.
We need to see permanently upgraded municipal electric grids. Dedicated AI institutes at local community colleges. Standardized apprenticeship programs that route local residents into high-paying technical careers. Sovereign compute resources reserved for regional universities and homegrown startups. Local venture funds backed by tech capital to help residents build businesses using the very systems their town is hosting.
In short: Leave something meaningful behind.
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None of this is philanthropy. It is an active investment in the social license to operate — the intangible asset upon which every transformational technology ultimately depends. Lose that public trust, and projects stall, local regulations multiply, zoning boards revolt, and expansion grinds to a halt. The AI industry is not immune to public backlash simply because its technology is extraordinary.
America will build astonishing AI systems over the next decade. I have zero doubt about our engineering capacity. The far more critical question is whether we will build a country that still believes those systems are working in its favor.
History has a stubborn habit of answering that question long before the engineers finish training the next model.
