Goldman Sachs is flagging a less obvious but potentially decisive constraint on the artificial intelligence boom: the physical infrastructure that supplies electricity to data centers. While AI models and computing hardware continue to advance rapidly, the grid connections, power generation, and utility investments needed to support them operate on much longer timelines, creating a bottleneck that could slow the industry's growth.
According to Goldman Sachs Research, global data center power demand is projected to increase by 170% between 2025 and 2030, with the United States accounting for more than 60% of that growth. However, supply-chain constraints, permitting requirements, and limited grid capacity could moderate the pace of expansion.
“Power is probably the forever bottleneck,” said Jason Tofsky, global head of Digital Infrastructure Investment Banking at Goldman Sachs. He noted that delivering a successful project requires coordination across numerous areas, including financing, over a period that can range from six months to two years.
AI growth depends on more than computing capacity
The AI industry requires substantial investment in computing hardware, data centers, and power infrastructure. Goldman Sachs estimates that aggregate AI capital expenditure could reach $7.6 trillion between 2026 and 2031 across these areas. Financing this expansion will require substantial borrowing alongside other sources of capital. Goldman Sachs Research projects that global hyperscaler debt issuance will reach $420 billion in 2027, more than 60% above its estimate for the 2026 financial year. Hyperscalers, however, account for only around 40% of credit raised across the AI ecosystem, highlighting the broader financing requirements associated with the industry's expansion.
These investments depend on more than the availability of capital. Data center developers must secure land, obtain regulatory approvals, source equipment, arrange electricity supply, and complete construction before facilities can become operational. The process creates multiple potential bottlenecks. Delays in any one area can affect the entire project, regardless of how quickly AI models or computing hardware improve.
Grid capacity emerges as a critical constraint
The US electricity grid faces growing pressure as data center developers seek access to large amounts of power. One challenge is the volume of projects waiting to connect to the grid. According to Goldman Sachs, the US interconnection queue contains roughly 2,600 gigawatts (GW) of generation and storage projects—more than twice the installed capacity of the existing grid. The size of the queue does not mean all proposed capacity will be built, but it illustrates the scale of demand competing for access to grid infrastructure. The median time between submitting an interconnection application and reaching commercial operation is now approximately five years, with some projects taking longer.
Transmission infrastructure is another constraint. Goldman Sachs Research data show that US construction of new high-voltage transmission lines declined from an annual average of 1,700 miles between 2010 and 2014 to just 350 miles between 2020 and 2023. Equipment shortages can extend the timeline further. Environmental reviews may take three to four years, while lead times for high-voltage substations and generation step-up transformers have stretched to roughly three to five years.
Utilities face rising investment requirements
The growing demand for electricity is changing the outlook for utilities, a sector traditionally associated with relatively low growth and defensive investment characteristics. Goldman Sachs expects aggregate utility capital plans to reach $1.3 trillion between 2026 and 2030. The projected spending reflects the need to expand infrastructure to accommodate rising electricity demand, including that generated by AI data centers.
Utilities must determine how to finance new generation capacity, transmission lines, and substations while ensuring that infrastructure can support additional large-scale electricity consumers. Hyperscalers and other large electricity users are increasingly considering arrangements in which they contribute directly to the cost of the generation and grid infrastructure required to serve their facilities. These arrangements could help align investment in digital infrastructure with the capacity needed to supply it.
Tyler Miller, global co-head of Power, Utilities, and Infrastructure Investment Banking at Goldman Sachs, described the principle behind this approach as straightforward: “Growth enables growth.” The idea is that investment in data centers can support additional investment in electricity infrastructure, provided that the costs and benefits are appropriately coordinated. For utilities, the opportunity is accompanied by substantial execution and financing requirements. Capital must be committed to projects that may take years to complete, while developers must manage equipment availability, regulatory approvals, and uncertainty over the timing of future demand.
Behind-the-meter power offers an alternative
The constraints affecting grid connections have encouraged greater interest in alternative power arrangements, including behind-the-meter projects. A grid-connected data center must secure the necessary approvals to connect to the electricity network. Behind-the-meter projects can avoid some of these grid constraints by arranging power supply outside the conventional grid connection process. However, these projects do not eliminate the broader challenges associated with building power infrastructure. They may face air-permitting requirements and longer environmental reviews, depending on the project.
This article is for informational purposes only and does not constitute financial advice.
