Last week’s seismic US midterm election results raised questions about the future of data centers, a core component of AI infrastructure. The top seven states leading data center development (Exhibit 1) will have Democratic governors in 2027, and the underlying assumption is that these governors will impose moratoriums on or otherwise restrict data center development in response to widespread, bipartisan community pushback. This means America’s AI ecosystem could be facing a patchwork of new state-level regulations in the years to come.1
As of November 2026
Source: BloombergNEF, DC Byte. Capacity reflects the power draw of the server equipment in a data center, before other functions such as cooling.
With election results in hand, markets began to recalibrate expectations for the pace and duration of data center buildouts and the effects on the broader tech sector. The Philadelphia Semiconductor Index (SOX) fell 15% in two days after the election as investors worried that prices, margins, and earnings expectations would fall due to slowing demand growth. Share prices also fell for key companies in the industrial and energy supply chain that could see similar demand slowdowns.
But my take is that the recalibration might potentially be positive in the long term. Why? Because slowing data center development could mitigate input shortages, which would lower costs and raise returns on AI investments. Put another way, incremental regulation, if measured, could reduce the risk of an AI bubble that ultimately bursts.
For over a year, I have worried that the modus operandi among US AI-related companies has been to spend as much as possible as quickly as possible to maintain the lead in the AI race, with less concern for the path to an attractive return on capital. This spending frenzy has led to bottlenecks, shortages, and sharp price increases for key components and services. Semiconductor prices rocketed, as did the profit margins of the producers—and as costs escalated, the prospects for many customers’ future profitability dimmed.
Additionally, while extended development timelines are widely assumed to increase costs, I believe the opposite could be true. Slowing demand for the services and products underlying data center buildouts—like construction workers and equipment, energy provision, and semiconductors—could lead to lower prices, as providers have more time to increase production capacity and reduce input shortages. Not every company would benefit from this shift. In fact, some providers of critical components and services will lose the ability to charge inflated prices that have led to surging profit margins. But in general, lower costs could make returns on investment more attractive for the key AI model developers and hyperscalers building out capacity to accommodate surging AI utilization.
It is also worth noting that many data center buildouts already in progress will not be affected by the election. Gubernatorial candidates were typically careful to indicate that previously approved projects would be allowed to proceed, meaning projects planned for 2028 and beyond are more likely to be impacted by the new regime than projects already in process.
Ultimately, I believe last week’s sell-off signaled a necessary recalibration of AI enthusiasm. With the S&P 500 trading at ~18x forward earnings expectations versus the five-year average of 19.8x and ten-year average of 19.1x, the risk of investing in US equities has decreased on the margin. Forward earnings forecasts likely still need to be reduced, but the recent declines provide a greater margin for error.
I still find emerging market and Japanese equities more attractive than US equities. But as the recalibration continues, I see equities in general becoming even more attractive relative to debt and other assets classes.
Important Information
Published on 11 November 2026.
1 With Democrats in control of both Houses of Congress, restrictions on the ability of state and local governments to regulate data center development are unlikely at the federal level.
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