AI in Cybersecurity for Aviation Webinar

Recent incidents like the Collins Aerospace breach highlight how attackers can access and exfiltrate sensitive internal data, including customer information and operational systems. Even with recovery measures in place, reinfection risks and incomplete visibility can prolong impact and expose deeper weaknesses. The lesson is blunt: incident response isn’t just about recovery, it’s about knowing your environment well enough to prevent attackers from coming back.

AI is lowering the barrier for attackers, enabling faster, more automated campaigns that previously required significant time and expertise. The same technology that improves efficiency for defenders is being used to scale phishing, reconnaissance, and intrusion attempts. Organisations must assume increased attack volume and sophistication, and adapt detection and response capabilities accordingly.

AI can process vast amounts of data quickly, but it lacks context and can produce confident but incorrect outputs, which in aviation can lead to serious operational consequences. Treating AI as a replacement for human expertise introduces risk rather than reducing it. The correct model is augmentation: AI supports analysis, but humans remain accountable for validation and final decisions.

Aviation systems are deeply interconnected across airports, airlines, and countries, making strict separation between IT and OT impractical. This connectivity improves operations and customer experience but significantly expands the attack surface and reduces visibility into critical systems. Security strategies must account for this reality by improving monitoring, context-aware decision-making, and collaboration between IT and operational teams.

Many organisations assume they are prepared because they have backups, but untested recovery plans and unmanaged devices can lead to reinfection and prolonged disruption. At the same time, delayed reporting of incidents or mistakes increases impact. True resilience comes from regularly testing recovery processes and building a culture where employees report issues early, supported by awareness of both traditional and AI-driven threats.