By Robert Rapier
Usually, the discussion about artificial intelligence focuses on chips, data centers, power plants, and electricity demand. All of this is important. However, another obstacle is beginning to emerge, which may have been underestimated so far.
The AI boom needs electricians. It needs workers, substation technicians, network engineers, plant engineers, welders, and construction crews. These are not jobs that can be filled immediately with a software update or a new round of funding. They require training, experience, and a steady stream of workforce that the electricity sector does not currently have on a large scale.
The AI boom isn't just a "digital story." There is also the physical infrastructure...
In the first phase of the development of artificial intelligence, the focus was on computing power. Investors turned to semiconductors, cloud service providers, and companies building massive data centers to support the workload required by AI.
Each of these facilities must be connected to the network. It must have transformers, substations, backup power generation, cooling systems, access to transportation, and workers with the appropriate qualifications to build and maintain this infrastructure.
And there the problem becomes complicated.
Reuters recently reported that the "rush" to build data centers is exacerbating labour shortages in the power and networks sector, especially in terms of electricians, engineers and professions related to procurement and construction. The problem is not that demand is increasing. But how is it increasing while a large percentage of experienced workers are approaching retirement age.
This condition creates a kind of constraint that investors are often asked to contemplate. A utility company can raise capital. A hyperscaler company can sign an electricity purchase contract. A manufacturer can order equipment. However, if there is no qualified staff, projects can be delayed.
Goldman Sachs Research estimates that electricity demand for data centers in the US could increase from 31 gigawatts in 2025 to 41 gigawatts in 2026 and 66 gigawatts in 2027. This will more than double the estimated capacity of data centers from the end of 2025 to the end of 2027.
Meeting this demand will require a massive expansion of production, transmission, interconnection and redundancy systems. Goldman Sachs also estimates that the U.S. power sector will need an additional approximately 510,000 workers by 2030 to meet growing demand, while Europe will need an additional 250,000.
These figures explain why the labour force issue may be a limiting factor. The electricity sector is not just competing with itself; Data centers, utilities, renewable energy developers, manufacturers, industrial projects, and grid modernization programs are competing to hire many of the same skilled workers.
The Bureau of Labor Statistics (BLS) predicts that the employment of electricians will increase by 9% from 2024 to 2034, an increased rate compared to the average for all occupations. It also predicts about 81,000 vacancies for electricians each year, many of which are linked to workers leaving the profession or retiring.
For electrical transmission line repairers, the BLS forecasts employment growth of 7% over the same period, also higher than average, with about 10,700 vacancies per year.
These are good jobs. But, it takes time to train a qualified electrician or transmission line technician, and more experienced workers are in demand for the most complex projects.
Costs, delays, and utility bills
The lack of a skilled workforce does not mean that the development of AI networks is stopping. It means that growth may become more costly and uneven.
Projects-partnerships with utilities will likely go ahead. Others may experience delays, cost overruns, or longer time frames for interconnection. The same pressure could also affect transmission grid upgrades, renewable energy projects, gas plants, and grid reinforcement works.
This has a direct impact on energy policy, utility customers and investors.
If utility companies need to build more infrastructure to serve large data centers, someone has to pay for it. Regulators are already concerned about whether the costs should be borne mainly by the large customers who "drive" demand or should be spread among all consumers. The labour shortage adds an extra dimension to this discussion, as higher construction costs are ultimately reflected in the economic viability of the projects.
That's why the boom of data centers is no longer just a technological issue. It now affects the regulation of utilities, the workforce in the construction sector, electricity markets and local economic development.
Who benefits?
For investors, the obstacle will likely be electricians, grid builders, equipment suppliers and utility companies.
Companies like Quanta Services, MYR Group, MasTec, EMCOR, Eaton, and Vertiv are much closer to the "physical" infrastructure side than most software companies. Labour shortages have a twofold impact. First, it can increase prices and boost the order portfolio, but it can also lower the speed of project completion. Second, the shares of most of these companies have rallied big over the past year.
The big picture
AI may be in the cloud, but the cloud needs to be built, powered, connected, cooled, and maintained. A model runs in the cloud. A chatbot answers a question. A search result appears immediately. But behind this experience is a chain of physical assets.
Chips may be attracting most of the attention. However, as electricity demand forecasts increase, power plants as well as natural gas turbines are attracting more and more interest. However, the labour force may become one of the most important limiting factors.
This is not an argument for or against artificial intelligence or data centers. It's an argument for understanding how the supply chain behind it all works.
The companies that are best positioned for the next phase of AI development may not be just those with the best chips or the largest data centers. It can be utilities, contractors, equipment suppliers, and infrastructure companies that have access to a skilled workforce and the ability to execute large projects.
The AI boom may be digital on the surface, but underneath lies a traditional manufacturing challenge. And in this world, electricians and production workers can be just as important as algorithms.
Forbes
