Artificial intelligence has quickly moved from the realm of science fiction into the center of economic and national policy. At a recent White House meeting with leaders from some of the largest technology companies in the world—including firms such as Google, Microsoft, Meta Platforms, Amazon Web Services, and OpenAI—Donald Trumpoutlined a strategy aimed at accelerating artificial intelligence infrastructure across the United States.
Much of the political conversation surrounding artificial intelligence focuses on algorithms, software, and digital innovation. But the meeting revealed something far more practical. Artificial intelligence requires enormous amounts of electricity, and electricity requires physical infrastructure.
Data centers that power AI systems consume far more energy than traditional computing facilities. Estimates suggest electricity demand tied to artificial intelligence could double or even triple over the next decade. The policy proposal discussed during the meeting attempts to address that reality by requiring technology companies to finance the power generation necessary to operate their AI facilities rather than shifting those costs onto the public electricity grid.
In simple terms, if companies want to build massive data centers, they must also help build the power plants and infrastructure required to run them.
From a policy perspective, the logic is straightforward. When private firms demand large amounts of energy infrastructure, the financial burden should not automatically fall on ordinary ratepayers.
Whether this approach succeeds will ultimately depend on outcomes rather than intentions.
For Black communities across the United States, the more important question is not who proposed the policy but what economic consequences it produces. History offers a clear lesson: major industrial expansions often occur around Black communities without necessarily including them in the economic gains.
Artificial intelligence has the potential to repeat that pattern unless communities focus on measurable results.
One of the most immediate opportunities lies in the skilled trades. The physical infrastructure required for AI data centers and power generation is enormous. These facilities require thousands of workers to construct and maintain them, including electricians, plumbers, welders, HVAC technicians, network technicians, and power plant operators.
Artificial intelligence may be powered by software, but it is built with pipes, wires, cooling systems, transformers, and mechanical infrastructure.
In other words, the AI economy will not only depend on computer programmers and software engineers. It will also depend heavily on skilled tradesmen.
This reality raises an uncomfortable question about the current direction of American education. For decades, the dominant message delivered to young people—particularly in urban school systems—has been that success requires a four-year college degree. As a result, vocational education and trade training were gradually pushed aside.
That decision had consequences.
Many industries now face severe shortages of electricians, plumbers, and HVAC technicians. These are not low-skill occupations. They are highly technical trades that require training, certification, and years of experience. They also offer incomes that often exceed the earnings of many college graduates.
The expansion of AI infrastructure will intensify this demand. Data centers require sophisticated cooling systems, advanced electrical installations, complex ventilation networks, and continuous maintenance. Power plants require skilled mechanical workers, welders, pipefitters, and technicians capable of operating large-scale industrial equipment.
These jobs cannot be outsourced overseas. They must be performed where the infrastructure exists.
If the United States intends to build the energy capacity and data center infrastructure required for artificial intelligence, the country will need a workforce capable of constructing and maintaining that system.
This is where education policy intersects directly with economic outcomes.
Schools that continue to push every student toward college while neglecting trade education are preparing students for a labor market that increasingly values practical technical skills. For many young people, particularly young men in urban communities, the trades may offer one of the most stable paths to economic mobility.
Black communities should therefore view the AI infrastructure expansion not simply as a technology story but as a workforce story.
If vocational programs, union apprenticeships, and technical training pipelines expand in Black communities, thousands of young people could enter well-paid skilled trades connected to the construction and operation of energy facilities and data centers.
If those pipelines do not exist, the projects will still be built. The jobs will simply go to someone else.
Another outcome worth watching is energy affordability. Many Black households already face disproportionately high energy costs relative to income. If technology companies truly finance the energy infrastructure required for their AI facilities, electricity costs for residential consumers could stabilize or even decline over time. If the costs ultimately shift back onto ratepayers through regulatory structures, the promise of “ratepayer protection” will prove largely symbolic.
Local economic development is another factor. Data centers require land, infrastructure, and proximity to energy supply. Many of these projects will be built near working-class communities where land and industrial zoning are available.
The relevant question is whether those communities receive meaningful economic benefits—jobs, training opportunities, and tax revenue—or whether they simply host facilities that generate wealth elsewhere.
None of these questions will be resolved by political speeches. They will be answered through measurable results.
Artificial intelligence is widely described as the defining technological transformation of the twenty-first century. That may well be true. But technological revolutions alone do not determine who prospers. Institutions, education systems, and workforce preparation often matter more.
For Black America, the critical issue is not whether artificial intelligence will reshape the economy. It almost certainly will.
The critical issue is whether our education systems prepare young people to participate in building that economy.
If schools continue to ignore the skilled trades, many young people will watch the infrastructure of the future rise around them while others fill the jobs required to build it.
Public policy should ultimately be judged not by the enthusiasm surrounding it but by the outcomes it produces. Employment levels, trade apprenticeships, energy costs, and local economic development will tell us far more about the success of this AI expansion than any announcement delivered in Washington.
Yes. Building trades offer an alternative in the AI economy. But I think there’s a middle ground that liberal arts college education still offers.
I had vocational education in high school and it was great but I later went to college.
We need to focus on high paying jobs that ai cannot do like health care and trades.
The problem with the trades is rampant discrimination and network effects. It’s really about who you know.