America First in the Age of Artificial Intelligence

DEVELOPING A POLICY FOR AI THAT FAVORS THE CITIZENRY?

An Interpretive Analysis of President Trump’s State of the Union Remarks on AI Infrastructure

When Donald Trump addressed artificial intelligence during his State of the Union and indicated that AI companies operating in the United States must secure their own electrical generation rather than rely upon the existing public grid, the remark passed quickly in the news cycle. Yet it deserves more careful consideration than it received. In a political environment saturated with technological enthusiasm and geopolitical alarmism, the President’s position signaled something far more grounded: artificial intelligence, however transformative, remains subject to economic reality.

Artificial intelligence is often described as a digital phenomenon—cloud-based, virtual, immaterial. In truth, frontier AI is intensely physical. It requires extraordinary electrical loads, industrial-scale cooling systems, semiconductor fabrication, and transmission capacity measured in hundreds of megawatts. A single hyperscale data campus can consume electricity equivalent to that of a small city. The American electrical grid, much of which was constructed in the mid-20th century, was not engineered for dense clusters of energy-hungry computational facilities.

The critical question, therefore, is not whether AI will grow—it will—but who bears the cost of accommodating it.

In traditional utility economics, large new industrial loads often require grid reinforcement. Transmission lines must be expanded, substations upgraded, generation capacity increased. Although industrial customers may pay interconnection fees, the broader cost structure frequently disperses across ratepayers through regulated utility adjustments. Residential consumers and small businesses absorb portions of the upgrade burden indirectly.

Had the President chosen the politically effortless path, he might have framed AI expansion as a national imperative requiring immediate grid access and public facilitation. Instead, by stating that AI firms must “find their own power,” he altered the burden of responsibility. Rather than socializing the cost of hyperscale expansion, he shifted it back to private capital.

This posture carries significant economic implications. It distinguishes AI from mid-century industrial expansion. When automobile manufacturing scaled across America after World War II, public infrastructure investments supported enterprises that directly employed thousands of workers and sustained entire supplier ecosystems. The social return on public investment was broadly distributed across the middle class.

AI infrastructure does not operate under the same employment model. It is capital-intensive and labor-light. It produces high-wage, highly specialized positions, but not broad industrial payrolls. Without constraint, its infrastructure expansion more closely resembles the financial sector’s concentrated growth patterns than the labor-distributed manufacturing boom of the postwar era.

For that reason, the President’s stance complicates a common criticism leveled by Democratic leadership—that he governs primarily in the interest of billionaires. The AI sector is dominated by some of the wealthiest corporations in the world. If favoritism were the objective, the easiest course would have been to guarantee expansive grid access, encourage federal subsidy, and smooth regulatory obstacles at public expense. Instead, the message was unmistakable: build your own generation.

Economically, that decision transfers infrastructure risk from households to capital holders. It protects residential ratepayers from upward pressure on utility bills. It reduces the likelihood that transmission congestion or grid instability will be absorbed by communities rather than corporations. Most importantly, it disciplines speculative overexpansion by forcing firms to internalize their energy requirements as capital obligations rather than marginal expenses.

Constraint is rarely the language of favoritism. It is the language of accountability.

There is also a second-order technological effect. For years, frontier AI competition has largely followed a brute-force model: larger parameter counts, more GPUs, bigger clusters, and escalating power consumption. When electricity is treated as an incremental cost, scale becomes the primary competitive lever. However, once generation capacity must be financed and constructed, efficiency becomes economically decisive.

History demonstrates that energy constraint often accelerates innovation. The oil shocks of the 1970s catalyzed advances in fuel efficiency. Early computing hardware limitations produced elegant and compact software engineering. Material scarcity during wartime has repeatedly forced breakthroughs in industrial design. If AI firms must directly bear the capital cost of power generation—whether natural gas, nuclear, or other sources—they will have powerful incentives to optimize model architectures, reduce redundancy, and improve inference efficiency. In that sense, energy realism may produce smarter systems rather than simply larger ones.

The broader economic question remains whether AI contributes meaningfully to American prosperity. Its value does not lie primarily in direct employment. Instead, its promise rests in productivity spillover: optimizing manufacturing systems, strengthening logistics networks, improving energy grid management, accelerating drug discovery, enhancing defense capabilities, and streamlining bureaucratic inefficiencies. If AI remains confined to speculative valuation cycles and digital services, its contribution to wage growth will remain limited. If integrated into domestic industrial production, its multiplier effect could be substantial.

By tying AI expansion to physical energy infrastructure, the President situates it within the same industrial framework that governs steel, petrochemicals, and heavy manufacturing. Innovation remains welcome, but it must operate within the constraints of energy sovereignty and fiscal discipline. This alignment is consistent with a broader America First philosophy emphasizing domestic production, infrastructure realism, and protection of citizens from hidden economic burdens.

The American system of federalism further complicates the matter. Utility regulation, environmental review, water rights, and zoning authority are distributed across federal, state, and local jurisdictions. Requiring AI firms to construct generation capacity respects this layered authority rather than overriding it. Energy-rich states gain competitive advantage. Grid stability remains protected. Infrastructure decisions remain grounded in local accountability rather than nationalized mandates.

In this light, the State of the Union remark reveals a coherent economic position. Artificial intelligence will not be permitted to expand in a manner that transfers its infrastructural strain onto American households. It must stand on its own industrial foundation. Even the largest corporations in the modern economy are expected to internalize their operational costs.

That approach undermines the simplistic assertion that the President “only supports billionaires.” In one of the most capital-concentrated sectors in existence, he declined to socialize cost and instead demanded self-sufficiency. Citizens, not hyperscale firms, were placed first in the risk hierarchy.

Artificial intelligence may reshape the economy. Yet greatness in any era depends not on abstraction, but on the disciplined alignment of innovation with national strength. By insisting that AI power itself rather than draw invisibly from public infrastructure, the President reaffirmed a central principle: American households and American sovereignty come before corporate expansion.