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CAA maps 200 aerospace AI uses as assurance challenges grow

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Photo: Pixabay | Wikimedia Commons

The UK Civil Aviation Authority (CAA) has identified reliability and human oversight as growing concerns as artificial intelligence expands into more complex aerospace work, including engineering and air traffic support.

The regulator analysed more than 200 aerospace AI use cases and consulted stakeholders during its summer 2026 research. It published the findings on 10 November as a baseline for tracking where the technology is being used and what wider adoption could mean for aviation safety and regulation.

The CAA found that current use is most visible in operational planning and optimisation, maintenance support, security screening and customer service. It also identified growing use in airport operations and engineering, including digital twins, which are virtual representations of physical assets or systems.

What aerospace firms need to demonstrate

The CAA highlighted assurance as an increasingly important part of adoption. For a company introducing an AI tool, that means building evidence that it performs reliably in the conditions in which staff will use it. The research also highlights the importance of how people work with the technology, particularly as it takes on more complex tasks.

A maintenance planning tool, for example, could flag a component for closer inspection. The question for the company is how staff assess AI recommendations and handle conflicts with other evidence. The consequences of an AI error depend on how its recommendations are used and which decisions the technology informs.

CAA Aerospace AI landscape infographic
Infographic: CAA

The CAA places advanced autonomy and future flight concepts among potential opportunities. Its published findings suggest that some of the challenges ahead will require co-ordination between industry, regulators, standards bodies and international partners.

The Aerospace Technology Institute and Capgemini reached a similar conclusion in their July research on UK aerospace manufacturing. They identified data quality, digital infrastructure, workforce skills and governance as conditions for wider adoption. They also stressed the continuing role of engineering judgement as manufacturers apply AI to work such as design, validation and production.

UK trials put AI to work

The CAA is testing AI in its own safety reporting workflow. The pilot examines whether AI can help staff sort and label mandatory occurrence reports, which record events that could impact aviation safety. Consistent classification could help safety specialists group similar events and identify patterns.

A separate example is Operation Blue Skies, a £5 million programme backed by the Department for Transport through the Aerospace Technology Institute Programme. The project will test whether small changes in flight altitude can help commercial aircraft avoid conditions that produce persistent warming contrails in the North Atlantic.

Google is developing AI models to predict where those contrails could form. NATS says the planned altitude changes will be co-ordinated through established air traffic control channels. Testing in Shanwick oceanic airspace is planned for two winters, 2026–27 and 2027–28. The trials are designed to assess both the feasibility of making the changes during normal flight operations and their environmental effect.

The CAA is inviting organisations deploying AI to share their experience as it continues to monitor developments. Its existing strategy for regulating AI and advanced automation sets out how it intends to support innovation while maintaining aviation safety and consumer protection.



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