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Energy Companies Outperform Big Tech Stocks Amid AI Boom
The seven largest energy companies gained an average of 38.5 percent in 2026, compared with just 18 percent for tech's Magnificent Seven, as investors increasingly bet on power and fuel suppliers for data centers rather than AI model makers.
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Record-breaking Big Tech spending on artificial intelligence infrastructure is not translating into the best stock market returns for the tech giants themselves. Instead, the companies profiting are those supplying them with raw materials and energy, and the gap in returns is already becoming hard to ignore.
Who's Profiting From the AI Boom
An analysis prepared by Ole Hansen, head of commodity strategy at Saxo Bank, compares the performance of the seven largest oil and energy companies, ExxonMobil, Equinor, ConocoPhillips, Shell, TotalEnergies, Chevron and BP, with that of the tech-focused Magnificent Seven, which includes Meta, Amazon, Apple and Tesla, among others. The conclusion is unambiguous: in 2026, energy companies delivered markedly higher returns for investors.
The average annual return of the seven energy companies came to 38.5 percent, more than double the 18 percent posted by the tech giants. The year-to-date figures are equally telling: Equinor has gained 71 percent, and every other company in the energy group has risen at least 25 percent. By comparison, Apple rose 19.6 percent, while Tesla lost 20.8 percent of its value.
A Math Problem That Doesn't Add Up
The source of this gap is a widening chasm between the scale of investment in AI infrastructure and the actual revenue generated by AI-based products. The largest tech companies are estimated to spend as much as $760 billion this year on expanding data centers and computing capacity, while direct revenue from AI products is estimated at just $80 to $150 billion.
Individual giants' financial results confirm the scale of this burden. Meta grew second-quarter revenue by 28 percent to $60.8 billion, but with capital expenditures of $31.1 billion, its free cash flow shrank to $784 million. The company expects full-year capital spending of $130-145 billion. Amazon, meanwhile, despite AWS cloud segment operating profit rising from $10.2 billion to $16.6 billion, is posting negative free cash flow of minus $7.6 billion on a trailing 12-month basis, with infrastructure purchase spending up by a further $66.1 billion.
Energy as the Bottleneck
Increasingly, it is not chip availability but electricity availability that is becoming the main constraint on AI development. Power demand from data centers is growing at a pace that electrical grids, averaging 40 years old in the US, cannot keep up with without massive investment in new infrastructure.
On top of that come purely commodity-driven factors. The US 3-2-1 crack spread refining margin has risen to $63 per barrel, up from about $25 a year earlier, and the diesel premium in Europe has topped $105 above the price of crude oil, compared with around $28 a year ago. Supply disruptions tied to the geopolitical situation, along with a sharp jump in refining and gas sector margins, are giving energy companies an immediate boost in cash flow, while tech giants grapple with rising AI investment costs and uncertainty over future returns.
In Europe, the situation is even more strained: natural gas there costs the equivalent of $142 per barrel of oil, more than $45 above Brent crude and roughly eight times more expensive than in the United States. That is further driving up energy costs for European industrial users, including data center operators.
What It Means for Investors
For investors, the takeaway from Saxo Bank's analysis is simple: exposure to the AI boom doesn't have to mean buying shares of companies that build language models or chips. More and more capital is flowing toward intermediaries, energy producers, grid operators, and gas and fuel suppliers, who profit from the infrastructure itself regardless of whether any particular AI model succeeds commercially.
This marks a reversal of the previous pattern, in which companies directly associated with artificial intelligence attracted the most attention and capital. Growing doubts about how quickly Big Tech's massive capital expenditures will pay off are prompting some investors to look for more predictable sources of profit along the AI supply chain, rather than betting solely on the model makers themselves.
For Poland's energy and investment markets, this data is both a warning sign and an opportunity. The growing demand for electricity from data centers, which domestic grid operators are also flagging, fits the same global trend of value shifting from AI developers to energy infrastructure providers.
