AI Doesn’t Just Need Chips. It Needs Gas.

According to CNBC, Baker Hughes CEO Lorenzo Simonelli says the company has seen zero slowdown in major energy project commitments, even as borrowing costs remain high by recent historical standards. The surprise isn’t that energy companies are still spending. It’s why they’re spending, and what that says about where the next decade of infrastructure dollars is actually going.

The short answer: artificial intelligence. Data centers that power AI workloads consume enormous amounts of electricity, and a growing share of that electricity runs on natural gas. That’s pushing LNG demand forecasts higher, which in turn is unlocking capital commitments for liquefaction projects, pipelines, and related equipment. When a Baker Hughes can point to AI as a demand driver for LNG, it tells you something about how structural the AI buildout really is. This is a capital allocation story, and the money flowing into it is patient, long-duration money, the kind that doesn’t spook easily over a quarter-point in borrowing costs.

Here’s the tension worth watching: long-term interest rates are currently sitting in the upper range of their history, conditions that have historically made project finance more expensive and, sometimes, more selective. Yet Simonelli is seeing the opposite. That probably means the demand signals are strong enough to justify the higher cost of capital, which speaks to the size of the opportunity the market is pricing in. It’s also consistent with credit spreads sitting near historic lows, meaning lenders aren’t demanding a risk premium to fund these deals.

Historically, investors have viewed a major services company’s order book and forward commentary as a real-time read on where industrial capital is actually being deployed, separate from the equity narratives that travel faster. When a company this deep in the project supply chain says pipelines aren’t drying up, that’s a data point worth putting next to GDP and sentiment surveys. The question it raises is whether AI-driven energy demand is durable enough to sustain this investment cycle if rate conditions stay elevated or tighten further.

Bottom Line: The AI infrastructure buildout has a gas problem in the best possible sense: it needs more of it, and that demand is now showing up in the real-world order books of energy equipment companies.

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