By Daily Touch Insights Editorial Team
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BUSINESS & ENERGY — Elon Musk built much of his public image around accelerating the transition away from fossil fuels. Tesla helped make electric vehicles mainstream, while Musk spent years promoting batteries and solar power as part of a cleaner energy future.
Now, the growing electricity demands of artificial intelligence are pushing Musk's business empire in a very different direction.
SpaceX and its expanding AI operations are increasingly relying on natural-gas-powered generation, while Musk has personally acquired a company that makes mobile gas and diesel turbines. The shift highlights a difficult reality of the AI boom: enormous computing power requires enormous amounts of electricity, and the fastest electricity available in many locations still comes from natural gas. 0
AI Has Created a New Energy Problem
The technology industry is entering an era in which electricity is becoming almost as strategically important as computer chips.
Training and operating advanced AI systems requires huge data centres filled with specialised processors. Those machines consume vast amounts of electricity and need reliable power around the clock.
Musk's companies are now attempting to build AI infrastructure at a scale that makes the electricity challenge impossible to ignore.
SpaceX's data-centre operations could eventually require as much as 15 gigawatts of power by the end of 2027, according to figures Musk discussed with investors. 1
Why Natural Gas Is Attractive
The problem is not simply generating electricity.
It is generating enough electricity quickly.
Connecting a massive new data centre to the electrical grid can require major transmission projects, new substations and regulatory approvals that may take years.
Natural-gas turbines offer a much faster alternative.
Companies can install generation directly at or near a data centre and begin producing electricity without waiting for large grid expansions.
This approach has become known as “bring your own power.”
Musk Is Embracing the Strategy
SpaceX is planning a massive chip manufacturing facility in Texas known as Terafab.
The project is expected to cost about $16.8 billion and cover roughly 100 million square feet.
The company plans to build a natural-gas power plant for the facility while also using electricity from the local grid and large battery systems.
The strategy reflects a simple calculation: getting power quickly can be more valuable than waiting years for traditional infrastructure.
The Gas Turbine Purchase Is Even More Significant
Earlier this year, Musk acquired APR Energy, a company specialising in mobile gas and diesel turbines.
The transaction was disclosed through regulatory filings and was reportedly worth around $1 billion.
APR's technology can provide mobile electricity generation, making it particularly relevant to data-centre projects that need power before permanent grid infrastructure is available. 2
The acquisition is striking because it places a fossil-fuel power business directly inside the portfolio of a technology entrepreneur whose most famous company was built around replacing gasoline-powered cars with electric vehicles.
Tesla's Original Mission Was Different
Tesla's early mission was centred on accelerating the transition toward sustainable energy.
Musk spent years arguing that transportation should move away from oil and toward electric power.
That vision helped transform Tesla from a niche electric-car company into one of the world's most influential automotive brands.
The new energy strategy surrounding Musk's AI businesses therefore represents a noticeable change in emphasis.
This Does Not Mean Musk Has Abandoned Clean Energy
The situation is more complicated than simply saying Musk has switched from clean energy to fossil fuels.
His companies are also pursuing solar power, batteries and space-based energy systems.
SpaceX has discussed the possibility of placing AI computing infrastructure in orbit, where solar energy could provide a continuous source of power.
Musk has argued that AI inference could eventually move into space while much of the training remains on Earth. 3
The immediate strategy, however, relies heavily on gas because the technology is available now.
Speed May Be Driving the Decision
The strongest explanation for the apparent contradiction is speed.
Building a solar farm, battery network or new transmission infrastructure at enormous scale takes time.
Natural-gas turbines can be deployed much faster.
For a company racing to develop AI systems, waiting several years for the electricity grid may be unacceptable.
That creates a practical choice between the energy system that is theoretically cleaner and the one that can deliver sufficient power immediately.
Other Technology Companies Are Facing the Same Problem
Musk is not alone.
Other major technology companies are also searching for ways to secure reliable electricity for rapidly expanding AI infrastructure.
Companies including Microsoft and Meta have pursued arrangements involving gas-powered generation and energy companies as they attempt to secure sufficient power for large computing facilities.
That suggests Musk's strategy is part of a much broader transformation in the relationship between technology and energy. 4
The AI Boom Could Increase Gas Demand
If AI data centres continue expanding rapidly, demand for electricity could rise substantially.
Where renewable energy and grid capacity cannot expand quickly enough, natural gas may fill the gap.
This could create an unusual outcome: a technology revolution often associated with digitalisation and automation could temporarily increase demand for one of the world's most important fossil fuels.
That does not necessarily mean fossil fuels will dominate the long-term energy system.
It does mean the transition may be less linear than many expected.
The Environmental Cost Is Becoming Harder to Ignore
Natural gas generally produces fewer carbon emissions than coal when generating electricity, but it remains a fossil fuel.
Large gas-powered data centres can therefore increase emissions while also creating local air-quality concerns.
The environmental consequences become more significant when temporary generators operate for long periods or when dozens of turbines are deployed at a single site.
That creates growing pressure for technology companies to demonstrate how their power strategies fit into broader emissions goals.
There Is Also a Business Argument
Reliable electricity is becoming a valuable commodity in the AI economy.
Companies that can secure power quickly may be able to bring data centres online before competitors.
That can translate into access to computing capacity, cloud contracts and additional revenue.
SpaceX's unconventional power strategy has already helped support major cloud-computing arrangements involving its AI infrastructure. 5
Power Could Become a Competitive Advantage
For years, the AI race was primarily described as a contest over chips and algorithms.
That description is becoming incomplete.
The companies capable of securing enough electricity, land, cooling capacity and network infrastructure may have a major advantage over companies that possess strong AI software but cannot obtain sufficient computing resources.
Energy is increasingly becoming part of the AI competitive landscape.
Musk's Contradiction Is Bigger Than Musk
It would be easy to portray this as simply an inconsistency in Musk's personal philosophy.
But the underlying problem is much broader.
The world wants rapid AI development while simultaneously trying to reduce carbon emissions.
Those objectives can conflict when electricity demand grows faster than clean-energy infrastructure.
Musk's businesses are simply operating at the extreme edge of that problem.
The Long-Term Bet May Still Be Renewable Energy
Musk's current dependence on natural gas does not necessarily mean he believes gas is the ultimate energy source for AI.
The strategy appears to be based on using whatever power can be deployed quickly while pursuing technologies that could eventually provide cleaner electricity at much larger scales.
Space-based solar power is one example of the more ambitious long-term ideas being explored by SpaceX.
The question is whether those technologies can become practical quickly enough to reduce dependence on gas.
The Risk Is Becoming Locked Into Gas
There is another possibility.
Once companies invest billions of dollars in gas turbines, pipelines and related infrastructure, they may have economic incentives to keep using those assets for many years.
Temporary solutions can therefore become permanent infrastructure.
That is why the environmental consequences of today's AI power decisions may extend well beyond the initial construction period.
Our Perspective
Musk's fossil-fuel shift should not be dismissed as simple hypocrisy, but neither should it be treated as irrelevant.
It exposes a genuine weakness in the current AI expansion model: the world's electricity infrastructure is not always prepared for the speed at which companies want to build computing capacity.
Natural gas provides a fast answer, but it comes with environmental and strategic costs.
The deeper question is whether AI will accelerate the transition to cleaner energy—or whether the race to build AI will temporarily make the world more dependent on fossil fuels.
Conclusion
Elon Musk's business empire is moving deeper into natural-gas power as the electricity requirements of AI become one of the biggest constraints on expansion.
SpaceX is planning gas-powered generation for its massive Texas chip facility, while Musk has acquired a company specialising in mobile gas and diesel turbines. His AI operations have also relied on gas turbines to supply power where the electrical grid cannot expand quickly enough. 6
The strategy stands in sharp contrast to the clean-energy image associated with Tesla and Musk's earlier advocacy for replacing fossil fuels.
But the shift also reveals a broader problem facing the technology industry: AI needs enormous amounts of reliable electricity, and the fastest way to obtain that power is often still fossil fuel-based.
Musk may have helped accelerate the electric-vehicle revolution, but the AI revolution is forcing him to confront an uncomfortable reality: the future of computing may depend on solving the energy problem before it can solve almost anything else.
