Countries and companies competing in the AI race are increasingly realizing they are also in an energy race. On some days, it seems as if AI is driving energy demand, with AI data centers representing the most significant new power demand growth in decades. On other days, energy appears to be driving AI, as the largest technology companies scramble to secure power and even vertically integrate to avoid external energy constraints.
Whether AI or energy is in the driver’s seat was a key question at the recent SAIT AI Summit in Calgary, Alberta—the energy hub of Canada. Executives from major energy companies spoke about leveraging AI tools while simultaneously working to supply the energy this transformative technology requires.
“Energy companies are in the unique position of deploying artificial intelligence internally to enhance operations, while also providing energy to data centers powering this transformational shift in technology,” said Lora Bucsis, Director of Product and Learner Success at SAIT. “Across our events and programs, we are seeing more integration and implementation of artificial intelligence at the executive level within the energy sector.”
### The Growing Overlap Between Tech and Energy
The increasing overlap between technology and energy is a welcome change for the energy sector. The largest companies in the world—from Alphabet to Meta—are now investing heavily into the physical economy. Commodities have not experienced a true capital expenditure (capex) boom in decades, but this trend is shifting. Goldman Sachs estimates that capex spending among the S&P 500 will accelerate by 17% next year, driven primarily by data centers and their associated power needs.
Although returns on AI investments have not yet matched the scale of spending, unique factors may sustain capital expenditures despite uncertain immediate returns. Governments view AI advantages as existential, which means they may continue to fund AI-related capex aggressively—even without proven outcomes. Historically, countries have often invested in fundamental shifts in economic or military capabilities without defined returns, and AI fits this pattern.
In fact, the White House released a briefing stating, “To remain the leading economic and military power, the United States must win the AI race.” Companies share a similar perspective: if AI is the last big platform shift or offers a permanent competitive advantage, the risks of underinvesting far outweigh the risks of overinvesting. Alphabet CEO Sundar Pichai has described AI’s potential as “as big as it gets.”
### Natural Gas: The Energy Sector’s Big Winner
Among energy sources, natural gas companies appear poised to benefit the most from this surge in AI-driven energy demand. It is notable that major gas hubs in Alberta and Texas have recently experienced negative gas pricing—an ideal environment for projects seeking low-cost, reliable power supplies. Delays in grid connectivity have also increased the appeal of on-site gas-fired generation and conversions to gas power.
“PJM and ERCOT are perfect examples of the natural gas bull story,” said Wish Bakshi, founder of AQ Energy, a consultancy specializing in data and AI applications for commodities trading, power plants, renewables, and LNG operations.
– **PJM:** Home to Virginia, the data center capital of the world, PJM is fast-tracking 10 GW of new generation capacity, with 70% focused on natural gas. Pennsylvania has positioned itself aggressively to attract AI data center investment by leveraging its massive Marcellus shale gas reserves to offer reliable, cost-effective energy supplies.
– **ERCOT:** In Texas, quick build permits and low prices at the Waha gas trading hub are attracting massive AI data center investments. The Stargate project in West Texas—a $500 billion initiative from OpenAI and Oracle—incorporates natural gas-fired power generation as its primary energy source. Likewise, Elon Musk’s xAI facilities, Colossus 1 and 2 in Memphis, Tennessee, utilize on-site gas turbines to generate power.
Other regions are focusing on smaller-scale gas projects that balance investor needs and regional demand. This approach also helps project owners address long lead times for larger turbines by opting for smaller turbines, which are more readily available.
### Rising Demand for Small Gas Turbines
S&P Global Commodity Insights has tracked this growing demand for smaller equipment. Over the past year, orders for small gas turbines dedicated to North American data centers have totaled about 1.9 GW. Including reciprocating engines and fuel cells, the total rises to approximately 3.2 GW. Manufacturers are responding: Mitsubishi, for example, has announced plans to double its gas turbine production to meet these needs.
Natural gas offers the speed and scale required to address rapid AI-driven demand growth. On-site turbines can be permitted and installed swiftly to meet project timelines, and the gas resource is established across North America at competitive prices.
### LNG Exports and Future Outlook
This surge in demand coincides with the maturation of LNG exports across North America, which is further accelerating natural gas demand. In a world dazzled by promising AI investments, natural gas stands out as a likely winner over the next decade, as energy executives increasingly find themselves collaborating with technology leaders.
As AI continues to transform industries and economies, the synergy between AI advancement and energy supply underscores an era where technological innovation and energy infrastructure development advance hand-in-hand.
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