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America must power AI with speed and discipline — or China will dominate
Latest

America must power AI with speed and discipline — or China will dominate

Last updated: March 3, 2026 8:13 pm
By
RNN
4 Min Read
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is reshaping the global economy, strengthening national security and redefining geopolitical competition. The hyperscale data centers that power AI are becoming as foundational to this century as railroads and interstate highways were to the last.

The Trump administration has made American leadership in AI a priority, accelerating permitting, securing energy supply and clearing barriers to critical infrastructure. That urgency is warranted. China has committed more than $125 billion to artificial intelligence, advanced computing and the energy systems needed to dominate emerging technologies. Beijing understands that whoever controls AI will shape markets and military capability for decades.

If the United States hesitates, not.

But speed without discipline invites backlash, and that backlash can quickly harden into and sometimes outright prohibition.

Across the country, AI data center projects are encountering growing resistance. In 2025 alone, at least 25 projects were canceled, four times more than the year before, eliminating gigawatts of planned capacity. Nearly 100 projects nationwide are now contested. Opposition spans party lines, from rural landowners to environmental advocates to ratepayer groups worried that rapid AI expansion will drive up electricity and water bills for local families.

In many communities, the central fear is straightforward: Big Tech will profit while residents pay higher utility costs.

In December, more than 230 environmental organizations urged Congress to impose a data center approvals. A moratorium would freeze investment, stall innovation and hand China a strategic advantage.

At the same time, community concerns are legitimate. Residents want to know whether data centers will strain local grids, raise electricity bills, increase water rates, divert scarce supplies, consume farmland or wildlife habitat and overpromise economic gains. When those questions are not addressed early, delay becomes the norm and cancellation the outcome. Nearly 40% percent of heavily contested projects ultimately fail. At a time of intensifying global competition, that kind of self-inflicted drag is a strategic mistake.

The choice is not between heavy federal regulation and ignoring local concerns. There is a better path rooted in market discipline, transparency and voluntary standards. 

Voluntary standards are not a concession to opposition; they are a strategy for sustaining durable public confidence, what some call a “social license to operate.” In a democratic system, infrastructure depends not only on permits but on continued public trust.

America learned this lesson during the early years of the shale natural gas boom. Producers that improved , reduced air impacts and engaged communities early were able to continue development. Where public confidence collapsed, moratoria and bans often followed. Trust, once lost, is far more difficult to rebuild than to establish from the outset.

AI infrastructure now faces a similar inflection point. If projects move forward without clear performance commitments, they risk becoming politically untenable. But if developers adopt credible, independently verified standards early, they can reduce uncertainty, limit conflict and accelerate responsible buildout.

Encouragingly, federal policymakers are exploring voluntary compacts with leading AI infrastructure providers. That model of partnership rather than prescriptive mandates can create national consistency without freezing innovation.

Developers should adopt independently verified standards for responsible AI infrastructure, with clear benchmarks for energy reliability, electricity affordability, water stewardship, responsible siting, community engagement and transparency. Congress and federal agencies can reinforce this approach by recognizing credible voluntary standards in permitting and infrastructure planning.

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