AI in Aviation Safety

A recent EASA survey found that aviation professionals are cautiously optimistic about AI in aviation safety, rating acceptance at 4.4 out of 7. Key concerns include performance limits, privacy, accountability, and the risk of de-skilling. Experts stress that human oversight, explainability, and regulatory frameworks must guide AI adoption in aviation. 

The aviation industry is exploring artificial intelligence (AI) as a tool to improve safety, efficiency, and predictive maintenance. But how ready are engineers, regulators, and operators to embrace it?

According to a survey conducted by the European Union Aviation Safety Agency (EASA), aviation professionals are cautiously optimistic. On a 7-point scale, overall acceptance of AI scored just 4.4, reflecting hope for innovation but concern about risks.

So what does this mean for aviation safety, and how can inspection technologies like borescopes help support AI-driven maintenance and oversight? Let’s break it down.

What the EASA Survey Reveals About AI in Aviation Safety

The EASA survey asked aviation stakeholders about AI’s potential benefits and risks. The findings:

• Moderate optimism: Acceptance of AI in aviation rated 4/7
• Top concerns:
  • Performance limits of AI
  • Privacy and data use
  • Accountability for errors
  • Risk of de-skilling human operators
• Clear requirement: AI must always operate under human oversight.

Respondents highlighted the need for explainability – AI systems must show how they reach conclusions- and the importance of building regulatory guardrails before scaling use in aviation.

Read the full EASA release here.

Why AI Oversight and Explainability Matter

For aviation professionals, trust is paramount. Engineers, pilots, and regulators agree: AI can never be a black box. Safety-critical systems demand transparent algorithms, reliable certification, and traceable data.

EASA’s AI Roadmap and the EU AI Act are working to define these frameworks, ensuring that human decision-makers remain accountable. The aviation industry will only adopt AI at scale if it strengthens, rather than replaces,  trusted safety processes.

Read all about the EU AI Act here.

Real-World Use Cases of AI in Aviation

While caution is high, AI is already being tested in several aviation applications:

• Predictive Maintenance – analyzing inspection data to identify component failures early.
• Traffic Management – optimizing aircraft routing to reduce congestion.
• Autonomous Systems – auto-taxiing and AI-assisted flight support.
• Troubleshooting with LLMs – AI-powered diagnostic support for technicians.

These applications align closely with the industry’s push toward efficiency and readiness, but only when paired with robust inspection data and oversight.

What This Means for Aviation Inspections and Borescope Technology

AI can only make safe, reliable predictions if it has accurate inspection data. That’s where borescope technology comes in.

• High-definition imaging provides the detailed visual data AI systems need.
• Digital recording and export ensure compliance with traceability standards.
• Predictive maintenance integration allows inspection results to feed AI models that flag defects before they become failures.

At SPI Borescopes, we understand that AI is not about replacing human expertise. It’s about enhancing it. Our inspection tools help aerospace maintenance teams capture the right data, ensuring AI-driven systems remain transparent, compliant, and effective.