Concerns over electricity bills and water use are turning into political action. Our Head of Public Policy Research Ariana Salvatore breaks down what the midterms mean for the data center pipeline, hyperscaler CapEx and investors. Read more insights from Morgan Stanley. ----- Transcript ----- Ariana Salvatore: Welcome to Thoughts on the Market. I'm Ariana Salvatore, Head of Public Policy Research at Morgan Stanley. Today, the U.S. midterm elections and what they could mean for the build-out of AI infrastructure. It's Wednesday, November 11th at 10am in New York. Growing concerns around electricity bills, water consumption, and the economic benefits of data centers have translated into meaningful political opposition. And last week's results reinforce just how salient those issues were in voters' decision-making. But what are the practical implications for the build-out? We think that the midterms were actually more likely to change where data centers get built, when they come online, and what cost is associated with doing so, rather than whether they get built at all. We've been flagging political opposition to data centers as a risk for some time, and the election results reinforce our view that this is largely a state-by-state and even project-by-project issue. Let's take a few examples. Texas, we think, was the most consequential result. Governor-elect Hinojosa has proposed pausing new data center approvals until stronger protections are in place. In Ohio, Governor-elect Acton has proposed a conditional moratorium. And in Georgia, we see policy action as more incremental, with greater scrutiny of construction approvals and how electricity infrastructure costs are allocated. So altogether, these developments point to a broader shift in political and community support. The opposition is increasingly bipartisan, but the friction remains primarily local. At the federal level, we think the government retains an accommodative posture, just given the importance of AI as national security infrastructure and the likelihood of a presidential veto on restrictive legislation. But what does this mean for the build-out? My colleague Cameron McVey and his team estimate that approximately five gigawatts of U.S. data center projects, or roughly 20 percent of the 2028 pipeline, will shift into 2029. We think 2027 construction will likely remain unaffected because projects are generally already permitted or underway. As a result, U.S. data center capacity additions are projected to be roughly flat in 2028 before growing nearly 40 percent in 2029. That feeds into our tech analyst view led by Brian Nowak that hyperscaler CapEx next year should remain unchanged at approximately $1.6 trillion and [$]1.8 trillion in 2028. So, our base case is a delay, not a fundamental reduction in investment. In fact, we think this could actually extend the duration of the AI investment cycle, and it reinforces an existing constraint – access to electricity. We've been highlighting the three Ps that are bottlenecks here: people, power, and politics. Stephen Byrd and our Powering AI team now estimate a 44-gigawatt shortfall in U.S. data center power through 2028, representing roughly 38 percent of projected demand. That means that the critical bottleneck is increasingly shifting from computing equipment to power data center facilities. And that has several investment implications. First, the largest and best-capitalized hyperscalers are particularly well-positioned. These are the companies that have a line of sight to 25 to 50 percent return on investment. They also have flexibility to redirect their investment, they can absorb higher costs, and they can improve computing efficiency. Second, we see opportunities in existing power-secured facilities and technologies that help developers access electricity more quickly. But there are also risks to the supply chain. A slower build-out in 2028 could mean weaker equipment orders, inventory accumulation, and pressure on supplier margins, even if the underlying AI demand remains strong Lastly, as my colleagues in credit like Vishwas Patkar have been highlighting, the financing environment is likely to become more differentiated under the surface. We continue to expect substantial AI-related borrowing in 2027 led by the hyperscalers. But new construction financing will face greater scrutiny around permitting, power availability, and execution. By contrast, existing data centers with stable cash flows could benefit from increased scarcity and stronger lease pricing. And finally, our equity strategy colleagues see investment opportunities broadening beyond infrastructure to companies actually adopting AI. So, the through line here is that midterms have introduced real political and execution risk. But we think that these constraints are more likely to reshape and actually prolong the AI investment cycle than derail it. And with the recent market weakness reflecting a more pessimistic outcome, we see selective opportunities across the AI value chain. Thanks for listening. If you enjoy Thoughts on the Market, please leave us a review wherever you listen and share the podcast with a friend or colleague today.
