This position paper provides the perspective of European Pilots and IFALPA on the development, use, and regulation of AI in civil aviation contexts.

A broad view and briefing, covering topics such as human perception and assistance systems, calibrated trust, creativity and intuition, human-centered systems design, data governance, cybersecurity, training, accountability, and flight data monitoring, is contained within the paper.

ECA and IFALPA, as the voice of the profession, believes that within this wide landscape there are three key, urgent challenges that need to be addressed politically or through regulation, if AI is to be an advantageous and successful addition to the aviation system.

Human Perception and Assistance Systems

AI assistance systems may enhance decision-making in future applications, but human perception and judgment remain essential. These systems should support, not replace, pilot input and decision making to avoid dangerous over-reliance on automated systems.

Trust in Assistance Systems

Successful implementation of AI in aviation requires calibrated trust, that means pilots must rely on systems appropriately without overconfidence or doubt. Transparency and traceability of AI decisions are key to building such balanced trust.

Creativity and Intuition

AI can process vast data but cannot provide human creativity and intuition, which are vital in unpredictable situations. Thus, AI should supplement rather than replace human problem-solving abilities in aviation.

System Design: The focus is on People

AI-supported systems in aviation should be designed around pilots, ensuring intuitive interaction, and preserving their decision-making authority while leveraging AI’s data-processing strengths.

Data Selection and Monitoring

AI systems in aviation must be trained on carefully selected, transparently collected data that reflect real operational practices without interfering with frontline work. Continuous oversight and periodic re-evaluations will be essential to keep systems aligned with evolving needs, while strict regulations ensure data privacy, fairness, and protection against misuse.

Data: Protection, Ownership and Privacy

Pilot-derived data must not be used for others’ commercial benefit, with strict safeguards in place to protect ownership rights and prevent exploitation beyond certified system use. Any possible usage of biomonitoring data requires transparency, voluntary participation, and strict protection to avoid ethical, legal, and privacy violations.

Cybersecurity Risks

in AI-Driven Aviation Systems AI-driven aviation systems face multiple cybersecurity risks, including data manipulation, privacy breaches, biased outcomes, insecure output handling, supply chain attacks, and AI-targeted cyberattacks. Mitigation requires robust security measures, real-time monitoring, explainable AI, and human oversight to maintain safety and system integrity.

Effects on training

In the future, pilots may need to combine traditional technical knowledge with the ability to work effectively use AI systems, while maintaining critical thinking, decision-making, and intuitive skills despite high automation. Also, where AI tools are used to support training , they must remain transparent, unbiased, privacy-protected, and accompanied by comprehensive instruction to ensure proper human oversight. Pilot performance evaluation should only ever be decided by trained pilots.

Control and Accountability in AI-Driven Aviation

As AI becomes more integrated into aviation, humans should retain executive control and accountability, with AI serving only as a support tool. Transparent, explainable AI, rigorous regulation, and continuous monitoring will be essential to ensure safety, allow human oversight, and maintain clear lines of responsibility.

AI in Flight Data Monitoring (FDM)

AI can enhance Flight Data Monitoring by efficiently detecting patterns, anomalies, and safety risks in large datasets. However, human oversight remains essential, as experienced personnel must interpret findings to ensure accurate context and actionable insights.

The future of civil aviation will be influenced by the integration of artificial intelligence. However, it is essential that the development of these systems not only takes humans and their unique abilities - such as perception, creativity and intuition - into account, but also specifically supports them, keeping them at the core of the system.

Maximizing the benefits of AI-usage in civil aviation will rely on the human ability to build systems that enhance, rather than replace, human judgment. This includes ensuring that AI systems remain a support tool whose authority and liability are commensurate with other certified aviation systems, that pilots retain full control and override capability, and that any automation fed by AI is fully transparent in how outputs are generated and the confidence levels attached to them.

Effective integration of AI will only be possible with highly transparent AI systems, full traceability of their decision-making, continuous effort to build calibrated trust in the new technology, dedicated pilot training on AI use, strong protection of data privacy and the ownership rights of the professionals who generate operational data, as well as cybersecurity awareness to address the existing risks. Any use of professional-generated data must have collective specific consent, be subject to clear regulatory safeguards, and include provisions for periodic oversight.

In the safety-critical domain of commercial aviation, the deployment of new systems or technologies and particularly any reliance on them must be approached with caution, ensuring they are fully understood by those who operate them and that robust mechanisms for oversight and control are in place before integration into operations.