Data centers aren't enough: The real AI infrastructure is people

The race to lead the AI economy has been just that: fierce competition for the most powerful chips, the largest data centers and increasingly sophisticated models. These investments, while essential, aren't enough on their own to ensure widespread ethical AI literacy and adoption. The greatest competitive advantage in the AI era will not belong to the organizations with the most computing power; it will belong to the workforce capable of using that power to its full potential. 

The question is no longer whether AI will change work; it's whether our institutions will prepare people quickly enough to lead that transformation rather than react to it.

Failure to equip rural and underserved communities with AI literacy resources is the greatest risk.

The most important infrastructure for any AI is the human behind the wheel.

Workforces across the country, including government offices, are increasingly using AI in their daily work. Law enforcement agencies are using AI-powered tools to improve communication with the public. Attorneys are accelerating legal research and managing growing caseloads. Manufacturers are optimizing production and quality control. Healthcare providers are using AI to support clinical decision-making. Farmers are improving productivity through precision agriculture. In each case, AI is not replacing these professionals -- it's allowing them to spend more time applying experience, creativity and judgment where it matters the most. 

Historically, this is exactly what leaps in technology do. Electricity did not eliminate manufacturing jobs; it fundamentally changed manufacturing. The internet did not eliminate commerce; it transformed how commerce operates. Now, AI is transforming knowledge work. Roughly 60% of today's workforce is employed in occupations that did not exist in 1940. AI is no longer just a tool; it is vital infrastructure for the next workforce remodel. Two-thirds of U.S. occupations will become at least partially automated by AI, according to research by Goldman Sachs. Waiting for this metamorphosis to start affecting our industries further and more intimately, without a plan, is not an option. If we treat AI as a shock, it will be a shock. 

For decades, infrastructure has meant classic civil engineering: roads, bridges, ports, airports and electricity. Then came the digital revolution of the internet and the connective powers of broadband. But an advanced AI economy's infrastructure requires advanced computing, trusted data and real people capable of translating AI discoveries into economic impact. Unlike our previous technological revolutions, AI requires both computational and human infrastructure to advance. Building these world-class computing facilities without investing in the people who will use them would be like building highways without training people to drive. The most important infrastructure for any AI is the human behind the wheel. 

Our federal government has embraced this mission, deploying national initiatives that integrate research, computing, workforce development, entrepreneurship and industry into one collaborative ecosystem rather than viewing these investments in isolation. Success in the AI race will not be measured by the number of GPUs installed or the size of a data center. It will be measured by whether those investments generate scientific breakthroughs, new companies, stronger industries and better jobs. By aligning with industry needs, we are equipping businesses with AI-driven solutions to their very real problems. But we must also equip our human workforce with the knowledge to properly program data and make their own assertions of AI-generated results. Relying on technology alone has never guaranteed economic leadership. Organizations need governance and frameworks that encourage innovation while protecting privacy, intellectual property, security, and public confidence. Responsible AI is the foundation for large-scale adoption. 

The objective is not simply to build better AI; it is to build stronger economies using AI.

The objective is not simply to build better AI; it is to build stronger economies using AI. It is to create better jobs, accelerate scientific discovery, strengthen existing industries, improve public services and expand opportunities for future generations. 

If we prepare people as intentionally as we prepare technology, we will do more than participate in the AI economy. We will define it.

Vasileios Maroulas, Ph.D., is associate vice chancellor for Next Generation Computing at the University of Tennessee, Knoxville, and executive director of AI Tennessee.