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A safer bet for AI-hungry investors

While some data center investors finance giant “behind the meter” power plants, others are looking for steadier returns in regulated grids.

A safer bet for AI-hungry investors

OpenAI’s decision to aid the construction of the largest fossil-fired power plant in the US reveals the massive scale of the AI energy race between major tech companies and their investors. Concerns about such projects turning into costly failures have prompted Wall Street firms to seek more stable investments in the power market.

The OpenAI project, involving OpenAI, SoftBank, the US government, and Nvidia, exemplifies the "bring your own power" approach advocated by the Trump administration for powering AI data centers without increasing costs for others. However, veteran investor Jeff Jenkins of Bernhard Capital Partners warns that this approach seems reminiscent of the early 2000s power plant investments that went wrong when deregulation failed to deliver expected electricity demand.

While the current AI boom seems more secure, Jenkins still prefers government-backed investments. In deregulated markets like Ohio, power plant operators compete on prices, while regulated markets like Louisiana and Florida have monopolies with fixed prices, leading to more reliable, but less spectacular returns. Bernhard Capital Partners has recently acquired several regulated utilities, including a Louisiana company with a contract to build a gas-fired power plant for Meta's Delta Forge 1 data center.

This shift towards purchasing regulated assets at discounted prices presents a lucrative opportunity for investors. However, the surge in private capital flowing into utilities raises concerns about the environmental impact of relying on gas for power and the potential for utilities to pass on the costs of new data centers to consumers.

Jenkins anticipates that once the current building boom is over, utilities will revert to buying back their previously sold assets at a profit.

Written by urgent.news from Semafor's reporting — not their text. Machine-written — may contain errors; check the original before relying on it.

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