Stefan Hirniak is the President of Specialist Staffing Group US.

The U.S. economy is transitioning from the post-pandemic era to a new phase driven by an artificial intelligence renaissance. A new generation of companies is attracting unprecedented investment in data centers, computing power, and the infrastructure needed to support the next stage of AI development.

However, for electric utilities, this investment brings new challenges: providing the grid infrastructure needed to support the rapid expansion of AI. The AI infrastructure race will not be won by capital and electricity alone. As utilities race to expand and modernize the grid, skilled engineers, technicians, and project leaders have become critical infrastructure in their own right. Without the workforce to build, operate, and maintain the grid, the AI economy simply cannot scale.

By one estimate, electricity demand from U.S. data centers is projected to reach 426 terawatt-hours by 2030, placing unprecedented demands on power generation, transmission, and grid modernization.

Yet, while much of the discussion focuses on power supply, transmission capacity, and capital investment, far less attention has been paid to the workforce required to deliver these projects.

Engineering teams are being asked to accelerate transmission upgrades, expand service connections, and modernize aging infrastructure, all while competing for an increasingly limited pool of engineers, technicians, and project leaders. The question is no longer just whether AI infrastructure can be financed, but increasingly: do we have enough people to build it.

Our analysis estimates that up to $1.4 trillion in U.S. STEM-related economic output could be at risk over the next decade if the talent pipeline fails to keep pace with growing demand. This makes workforce development not just a business challenge, but an economic imperative for America's long-term competitiveness.

Much of today's discussion rightly focuses on expanding generation, building transmission, modernizing the grid, and shortening interconnection queues. These challenges are real, and utilities are investing billions to address them. But even the most well-funded infrastructure projects cannot advance without the engineers, technicians, and project leaders needed to design, build, commission, and maintain them.

For utilities, this has become an operational challenge. Utilities across the country are investing billions to expand transmission networks, modernize substations, and strengthen the grid to support AI-driven electricity demand. These projects depend on highly specialized transmission engineers, protection engineers, relay technicians, and project managers. Even when funding, equipment, and permits are in place, shortages of qualified personnel can become the limiting factor determining how quickly critical infrastructure moves from planning to operation.

This challenge is even more acute for small and rural utilities, which often lack the resources to compete for specialized talent and replace retiring workers. Nearly half of U.S. engineers are aged 50 or older, and as experienced professionals retire, the knowledge gap becomes significant. Meanwhile, utilities are increasingly competing with hyperscale tech companies and data center developers for the same electrical engineers, technicians, and power systems experts. AI is not only increasing electricity demand, it is also reshaping the labor market itself, forcing utilities and tech companies to compete for the critical talent needed to build and operate modern infrastructure.

This should change how utilities think about workforce strategy.

Workforce planning should begin in tandem with capital planning. Before launching major grid investments, utilities need to ensure they have the engineers, technicians, and project leaders required to deliver projects.

Hiring alone will not solve the problem. Many of the skills needed to support AI-driven infrastructure already exist within today's utility workforce. Investing in upskilling, mentorship, and knowledge transfer helps preserve institutional expertise while preparing employees for increasingly complex grid operations.

Utilities also have the opportunity to strengthen the long-term talent pipeline through deep partnerships with universities, community colleges, vocational schools, and workforce organizations. For small and rural utilities that often struggle to compete for experienced talent, investing in local workforce development offers a more sustainable long-term solution than relying solely on an increasingly competitive hiring market. Expanding hyper-local pipelines now will lay the foundation for building a resilient utility workforce that can withstand attrition and create new opportunities for the communities that power America's energy future.

Regulators, educators, and legislators also have a role to play in supporting technical education, expanding apprenticeships and workforce development programs, and recognizing that workforce capacity in this field is critical to the long-term success of the U.S. economy.

Given how much is at stake for America's AI ambitions, workforce strategy should stand alongside generation, transmission, and capital planning. Investing in the U.S. energy workforce is essential to powering the AI economy and ensuring America has the people to build, operate, and maintain the infrastructure that now defines its economy.