The global market for AI in the sector is projected to soar to nearly USD58 billion by 2034, signalling a fundamental shift in how humanity operates beyond Earth.
As NASA’s Perseverance rover navigates the Martian terrain, making 88% of its driving decisions autonomously, a profound truth becomes clear: artificial intelligence is no longer merely used as a tool for space exploration, but is an increasingly independent actor. This technological revolution is enabling missions of unprecedented complexity and efficiency, from the autonomous construction of lunar bases under the Artemis programme to the AI-guided operations of deep-space probes like the Europa Clipper.
The erosion of 'fault' and the liability vacuum
This transition from human-assisted to machine-led operations, however, exposes deep fissures in the foundations of international space law. The core problem is a 'techno-legal disconnect': our international norms, codified in treaties from the 1960s and 1970s, were built around the paradigm of human conduct and direct control. They may suffer a cyber attack, function unpredictably, or fail entirely, when applied to the actions of autonomous AI systems. This creates a critical and dangerous 'liability gap', where a catastrophic failure caused by an AI could leave victims without a clear legal remedy. For businesses, investors, insurers, and States navigating this high-stakes domain, the implications are profound and demand immediate strategic attention.
The most acute legal crisis created by AI in space is the near-total erosion of the concept of "fault" as the basis for in-space liability. The 1972 Liability Convention, the cornerstone for addressing damage caused by space objects, establishes a two-tier system: absolute liability for damage on Earth (Article II) and fault-based liability (Article III) for damage occurring in space, such as a collision between two satellites. This fault-based regime (Article III) is now profoundly challenged.
The term "fault" is left undefined in the treaty, but its legal history points to a human-centric concept encompassing negligence, error in judgment, or a breach of a duty of care. Attributing such a state to an autonomous AI is a legal Gordian Knot. The challenge is twofold:
- First, the 'black box' problem means the decision-making processes of complex neural networks can be inherently opaque, even to their creators. Without a clear, auditable trail of the AI's logic, proving that a harmful action resulted from negligence in the AI's design or training - rather than as a result of an unforeseen but statistically valid outcome - becomes an exercise in speculation.
- Second is the foreseeability problem. Advanced AI is designed to learn and exhibit "emergent behaviour" - actions not explicitly programmed by its creators. If such behaviour causes a collision, the operator could argue the outcome was unforeseeable and that all due care was exercised, breaking the legal chain of causation required to establish fault.
This ambiguity creates a significant liability gap, leaving victims potentially without compensation. The legal uncertainty translates directly into commercial risk. Insurers will find it difficult to underwrite policies for highly autonomous missions when the key legal trigger is so ill-defined, potentially leading to prohibitive premiums or an outright refusal to insure. This, in turn, is directly linked to the principle of State Responsibility under Article VI of the Outer Space Treaty, which mandates "authorisation and continuing supervision" of national space activities. If a State cannot meaningfully supervise an opaque AI, its ability to prevent "fault" is compromised, creating an evidentiary barrier for any future claimant and magnifying the risk for all space actors.
Who owns the data?
The corpus of UN space law was drafted long before the era of big data and AI, and therefore remains largely silent on questions of data and information governance. Today, satellites do not merely collect raw data; they provide the training and operational backbone for powerful AI models. Systems such as Google’s AlphaEarth Foundations synthesise heterogeneous Earth‑observation sources into new, high‑value ‘information products’ - for example, precise land‑use/land‑cover maps, evapotranspiration estimates, or emissivity fields - that can be scaled globally with only sparse labels. These capabilities have tangible benefits: for industry, they enable precision agriculture, supply‑chain due diligence, infrastructure monitoring, and mineral prospecting; for individuals, they support early‑warning systems for floods or wildfires, improved crop forecasts for smallholders, and even consumer‑facing sustainability tools.
It has long been the case that technologies developed to support space exploration are quickly plundered for their commercial and broader benefits. Many things from memory foam to freeze dried food have their origins in the necessities of extraterrestrial travel. Now we see our presence in space harnessed more deliberately to collect wider datasets to feed purpose-built AI models. Yet this technological leap gives rise to novel legal questions for which the treaties offer no clear answers: who, if anyone, ‘owns’ AI‑derived insights (beyond traditional copyright or database rights)? And how can individual privacy be safeguarded when AI can infer ‘patterns of life’ from high‑resolution imagery? Are traditional privacy rights, focused as they are on the rights of the individual, appropriate to address the reality of groups of people being subject to scrutiny designed to predict their every move? The same technology designed to protect us in the event of major environmental threats could, for example, be used against us by government actors or indeed corporate bodies, with less benign aims and at present only the overstretched concept of individual privacy offers us any protection at all from such collective threats.
Charting a course for responsible governance
The transformation of the space sector by AI is irreversible. The legacy legal framework is no longer fit for purpose. The slow, consensus-based reform of UN treaties is not necessarily going to provide timely answers. In the meantime, and in the absence of supra-national consensus, the path forward is more likely to involve a pragmatic, multi-layered governance architecture that combines targeted treaty clarification, agile 'soft law' instruments like technical standards, and influential regional regulation.
