Satellites Are Multiplying Fast. AI May Be the Only Way to Keep Them Running
With up to 70,000 new satellites possible in the next five years, human operators alone cannot keep pace. A space industry veteran explains what AI can do in orbit, and why the rules haven't caught up yet.
Key points
- Goldman Sachs estimates up to 70,000 new low-Earth orbit satellites could launch within five years.
- AI could process satellite imagery in orbit, cutting the time between data collection and useful results.
- Current laws and insurance policies were written for human-controlled systems, leaving accountability gaps when AI makes a mistake.
- Gradual adoption is likely, with AI handling routine decisions first while humans approve the bigger calls.
- AI could also shorten spacecraft design and manufacturing timelines, letting smaller teams do more.
Right now, roughly 16,000 active satellites circle the Earth. Market researchers at Novaspace think 43,000 more will launch over the next decade. Goldman Sachs puts the figure even higher: as many as 70,000 new satellites in low-Earth orbit (the band of space a few hundred miles up, where most communications and observation satellites sit) within five years alone.
The exact count matters less than the trend. Constellations are growing fast, and the way humans manage them cannot keep up.
Why can't people just run them from the ground?
A handful of satellites is manageable. Thousands are not. Each one must share data with its neighbours, dodge interference, respond to shifts in customer demand and handle technical faults. Some decisions need to happen in seconds. Radio signals take time to travel between Earth and orbit, so waiting for a ground controller to notice a problem and send instructions back up is simply too slow.
Writing for Space.com's Expert Voices section, Martin Halliwell, a former Chief Technology Officer at satellite operator SES and now a partner at space-focused investment firm NewSpace Capital, argues this is where artificial intelligence (AI), software that can analyse data and make decisions on its own) becomes essential.
What would AI actually do up there?
Two jobs stand out. The first is data processing. Today, most raw satellite data travels back to Earth before anyone sorts or analyses it. An Earth-observation company tracking crop yields or wildfire smoke has to download enormous volumes of imagery and clean it up on the ground before a single useful number reaches a customer. If the satellite's onboard computer runs an AI model, it can do that filtering itself and send home only the relevant pieces. Faster answers, lower data costs, and less dependence on ground stations that could be knocked offline.
The second job is managing network capacity. Demand for satellite bandwidth, the amount of data a signal can carry, shifts constantly: over crowded cities, at disaster sites, above busy shipping lanes. An AI system could track those shifts in near real time, steer the satellite's signal beams toward wherever demand is highest and dial power up or down accordingly. A fixed, one-size-fits-all beam wastes capacity; a steered one gets more useful work from the same hardware.
Who is responsible when AI gets it wrong?
This is where the industry hits a wall. Laws, contracts and insurance policies were written assuming a named human makes every significant decision. When AI points a beam at the wrong location and disrupts another operator's service, it is genuinely unclear whether the blame falls on the satellite owner, the hardware manufacturer or the company that wrote the software.
Halliwell expects adoption to move in stages. Operators will likely let AI offer recommendations first, then gradually hand over more routine calls while keeping humans in the loop for anything consequential. Clear written rules about which decisions AI can make alone, and which need a sign-off, will be necessary before the industry moves faster.
AI could also reshape how satellites are built, helping engineers draft structures and run tests more quickly, so smaller teams can tackle projects that once needed much larger organisations. Skilled engineers stay essential; the goal is to free them from repetitive work.
What happens next?
The technology is arguably ready. The harder task is building the legal frameworks, cybersecurity standards and institutional trust to use it at scale. As Halliwell puts it, AI may soon be capable of running more of a satellite network. The real question is how quickly the industry is willing to let it.
Common questions
Does this mean satellites will fly with no human control at all?
No. The near-term picture is AI handling fast, routine decisions while humans approve anything significant. Full autonomy would require legal and regulatory changes that are still years away.
How does this affect ordinary people on the ground?
Faster disaster alerts, more responsive mobile coverage in remote areas and cheaper satellite broadband are the practical benefits if AI-managed constellations deliver on their promise.
