The Race to Build Data Centers in Space: Why Sam Altman and Elon Musk Are Looking Beyond Earth for AI’s Power Problem

The artificial intelligence industry is consuming electricity at a pace that has stunned even its own architects. Now, two of the most prominent figures in technology — Sam Altman and Elon Musk — are independently floating the idea that the solution to AI’s insatiable energy appetite may lie not on Earth, but in orbit above it. The concept of space-based data centers, once relegated to science fiction, is entering serious conversation among industry leaders, and the timeline they’re discussing is startlingly near.
According to Business Insider, Altman suggested during a recent appearance that data centers in space could become viable within a matter of years, not decades. Musk, never one to shy away from ambitious timelines, has echoed similar sentiments, pointing to the decreasing cost of launching payloads into orbit via SpaceX’s Starship rocket as a key enabler. The convergence of these two visions — from the CEO of OpenAI and the head of SpaceX and xAI — signals that the idea has moved from theoretical musing to something approaching strategic planning.
AI’s Electricity Crisis Is Accelerating Faster Than Anyone Predicted
The underlying driver of this conversation is straightforward: AI model training and inference require staggering amounts of electricity, and the demand curve is only steepening. Goldman Sachs estimated in 2024 that data center power consumption in the United States could more than double by 2030, driven almost entirely by AI workloads. The International Energy Agency has projected that global data center electricity use could reach 1,000 terawatt-hours annually by 2026, roughly equivalent to Japan’s entire electricity consumption.
This surge has already created bottlenecks. In Northern Virginia, home to the world’s densest concentration of data centers, utility provider Dominion Energy has warned of potential power shortages. Similar constraints are emerging in Texas, Ireland, and the Netherlands. Tech companies including Microsoft, Google, and Amazon have responded by signing long-term power purchase agreements, investing in nuclear energy, and even exploring geothermal sources. But these solutions take years to come online, and the demand for compute is growing faster than the grid can expand.

Altman’s Vision: Solar Power Without Clouds
Altman’s argument for space-based data centers rests on a simple physical advantage: in orbit, solar panels receive uninterrupted sunlight, unfiltered by atmosphere, weather, or nightfall. A solar array in space can generate roughly five to ten times more energy per square meter than one on Earth’s surface. For an industry desperately seeking abundant, cheap, carbon-free power, the math is compelling.
During his remarks, as reported by Business Insider, Altman framed the concept not as a distant aspiration but as something that could begin taking shape as early as 2026 or 2027. He pointed to the rapid decline in launch costs — SpaceX’s Starship is designed to bring the cost per kilogram to orbit down to roughly $10, compared with thousands of dollars per kilogram on legacy rockets — as the critical inflection point. If Starship delivers on its promise of frequent, low-cost flights, the economics of placing computing hardware in space begin to change dramatically.
Musk’s Dual Position: Supplier and Customer
Elon Musk occupies a unique position in this emerging discussion. As the founder of SpaceX, he controls the most advanced launch infrastructure on the planet. As the head of xAI, which is building massive AI training clusters, he is also one of the largest consumers of data center capacity. His Colossus supercomputer in Memphis, Tennessee — reportedly one of the largest AI training facilities in the world — already strains local power infrastructure.
Musk has spoken publicly about the possibility of orbital computing, noting that SpaceX’s Starlink satellite constellation already demonstrates the viability of placing sophisticated electronics in low Earth orbit at scale. Starlink operates more than 6,000 satellites, each packed with custom silicon and networking hardware. The leap from communication satellites to compute satellites, while enormous in engineering terms, builds on proven manufacturing and deployment capabilities that SpaceX has spent a decade refining.
The Engineering Challenges Are Formidable but Not Insurmountable
Skeptics — and there are many — point to a long list of technical obstacles. Cooling computer hardware in space is fundamentally different from cooling it on Earth; there is no air to carry heat away, so systems must rely on radiative cooling, which is less efficient and requires large surface areas. Radiation in orbit degrades electronics over time, necessitating either hardened components or frequent replacement. Latency between orbital data centers and terrestrial users would add milliseconds to every transaction, which matters for real-time applications.
There is also the question of maintenance. On Earth, a failed server can be swapped in minutes. In orbit, physical repairs require either robotic servicing or, more likely, replacement of entire satellite units. The economics only work if the hardware is cheap enough to be considered semi-disposable — a model that SpaceX has already pioneered with Starlink, where satellites are designed for a five-year lifespan and replaced continuously.
Startups Are Already Placing Bets
Altman and Musk are not the only ones thinking about this. Several startups have emerged in recent years with explicit plans to build computing infrastructure in space. Lumen Orbit, a Y Combinator-backed company, is developing satellites designed specifically for AI training workloads in orbit. The company argues that the combination of unlimited solar power and the natural cold of space (on the shaded side of a satellite) creates thermal advantages that partially offset the cooling challenges.
Another company, Axiom Space, is building commercial space station modules that could eventually host computing hardware. And the European Space Agency has funded research into orbital data processing as part of its broader strategy to reduce the terrestrial environmental footprint of digital infrastructure. These efforts remain small relative to the scale of the problem, but they represent real engineering work, not just PowerPoint slides.
The Financial Calculus: When Does the Math Actually Work?
The central question is economic, not technical. Can the cost of launching, powering, and maintaining computing hardware in space be brought below the cost of building and operating equivalent capacity on the ground? Today, the answer is clearly no. A single rack of high-performance AI servers costs tens of thousands of dollars; launching that same rack to orbit on a Falcon 9 would cost hundreds of thousands more, before accounting for the specialized enclosure, power systems, and cooling infrastructure required.
But the cost curves are moving in the right direction. SpaceX’s Starship, if it achieves its target economics, could reduce launch costs by one to two orders of magnitude compared with current options. Meanwhile, terrestrial energy costs for data centers are rising, not falling, as demand outstrips supply and utilities impose premium pricing on large industrial loads. If launch costs fall to $10 per kilogram and terrestrial electricity prices continue to climb, the crossover point could arrive sooner than conventional wisdom suggests.
Regulatory and Geopolitical Dimensions
Space-based data centers also raise novel regulatory questions. Which nation’s laws govern data processed in orbit? How are spectrum and orbital slot allocations managed for computing satellites versus communication satellites? What happens when a data center satellite reenters the atmosphere — who is liable for debris or environmental contamination?
Geopolitically, the concept has obvious national security implications. A country or company that controls significant computing capacity in orbit holds a strategic asset that is difficult to physically attack or regulate from the ground. This could accelerate the already intense competition between the United States and China over space dominance, adding a new dimension to the rivalry over AI supremacy.
A Timeline Measured in Years, Not Decades
What makes the current moment different from previous discussions about space-based computing is the specificity of the timeline. Altman and Musk are not talking about 2040 or 2050. They are talking about the late 2020s. Whether that proves optimistic or realistic, the fact that the leaders of OpenAI and SpaceX are publicly anchoring expectations to such near-term dates has a gravitational effect on investment, talent, and policy attention.
The AI industry has repeatedly demonstrated its ability to compress timelines that seemed impossibly ambitious. Five years ago, the idea that a chatbot could pass the bar exam or generate photorealistic video from text prompts would have been dismissed by most experts. The same compressive force may now be applied to the infrastructure that powers these models. If the electricity problem cannot be solved on the ground fast enough, the industry may have no choice but to look up.

According to Business Insider, Altman suggested during a recent appearance that data centers in space could become viable within a matter of years, not decades. Musk, never one to shy away from ambitious timelines, has echoed similar sentiments, pointing to the decreasing cost of launching payloads into orbit via SpaceX’s Starship rocket as a key enabler. The convergence of these two visions — from the CEO of OpenAI and the head of SpaceX and xAI — signals that the idea has moved from theoretical musing to something approaching strategic planning.

The underlying driver of this conversation is straightforward: AI model training and inference require staggering amounts of electricity, and the demand curve is only steepening. Goldman Sachs estimated in 2024 that data center power consumption in the United States could more than double by 2030, driven almost entirely by AI workloads. The International Energy Agency has projected that global data center electricity use could reach 1,000 terawatt-hours annually by 2026, roughly equivalent to Japan’s entire electricity consumption.

This surge has already created bottlenecks. In Northern Virginia, home to the world’s densest concentration of data centers, utility provider Dominion Energy has warned of potential power shortages. Similar constraints are emerging in Texas, Ireland, and the Netherlands. Tech companies including Microsoft, Google, and Amazon have responded by signing long-term power purchase agreements, investing in nuclear energy, and even exploring geothermal sources. But these solutions take years to come online, and the demand for compute is growing faster than the grid can expand.

Altman’s argument for space-based data centers rests on a simple physical advantage: in orbit, solar panels receive uninterrupted sunlight, unfiltered by atmosphere, weather, or nightfall. A solar array in space can generate roughly five to ten times more energy per square meter than one on Earth’s surface. For an industry desperately seeking abundant, cheap, carbon-free power, the math is compelling.

During his remarks, as reported by Business Insider, Altman framed the concept not as a distant aspiration but as something that could begin taking shape as early as 2026 or 2027. He pointed to the rapid decline in launch costs — SpaceX’s Starship is designed to bring the cost per kilogram to orbit down to roughly $10, compared with thousands of dollars per kilogram on legacy rockets — as the critical inflection point. If Starship delivers on its promise of frequent, low-cost flights, the economics of placing computing hardware in space begin to change dramatically.

Elon Musk occupies a unique position in this emerging discussion. As the founder of SpaceX, he controls the most advanced launch infrastructure on the planet. As the head of xAI, which is building massive AI training clusters, he is also one of the largest consumers of data center capacity. His Colossus supercomputer in Memphis, Tennessee — reportedly one of the largest AI training facilities in the world — already strains local power infrastructure.

Musk has spoken publicly about the possibility of orbital computing, noting that SpaceX’s Starlink satellite constellation already demonstrates the viability of placing sophisticated electronics in low Earth orbit at scale. Starlink operates more than 6,000 satellites, each packed with custom silicon and networking hardware. The leap from communication satellites to compute satellites, while enormous in engineering terms, builds on proven manufacturing and deployment capabilities that SpaceX has spent a decade refining.

Skeptics — and there are many — point to a long list of technical obstacles. Cooling computer hardware in space is fundamentally different from cooling it on Earth; there is no air to carry heat away, so systems must rely on radiative cooling, which is less efficient and requires large surface areas. Radiation in orbit degrades electronics over time, necessitating either hardened components or frequent replacement. Latency between orbital data centers and terrestrial users would add milliseconds to every transaction, which matters for real-time applications.