Enhancing Aviation Safety with Training, Operational Data

Training providers are capturing data during training events and combining this with operational data to improve pilot training outcomes, CAE senior manager of product management Clément Cateau explained this morning at Bombardier Safety Standdown 2025.  His presentation, “Enhance Safety Intelligence with Training Data,” explored how this data is being used to improve training and support safety management systems (SMS).

Just as aircraft operators use flight operational quality assurance to leverage aircraft data for SMS programs, so too are training providers with what is being called simulator operational quality assurance. This is all part of what Cateau identified as "safety intelligence…it’s about collecting data, transforming raw data into actionable insights for safety management systems.”

While Cateau’s presentation delved into various aspects of safety intelligence, one of the more interesting points he made was about the growing use of artificial intelligence tools in analyzing the data that is captured.

He said the goal of using training data to enhance safety intelligence is “knowing what happened, why it happened, and providing automatically the recommendations to all different stakeholders and organizations…in an automated way.” This is done manually now and isn’t very systematic, Cateau added. In the future, however, there should be automatic ways to provide feedback based on operations and training data, and draw profiles and other inputs. “But we’re not quite there yet.”

Where AI could help would be in that automation, but Cateau sees AI as an aid, not a replacement, for all the stakeholders involved in training (pilots, instructors, heads of training and safety, OEMs, and regulators). “It’s a powerful technology that we should definitely consider,” he said.

More specifically, he explained, AI can provide helpful information—for example, during a debriefing after a training session because it has access to more data and observations that an instructor might not have seen. When combined with eye-tracking tools, “it will also be beneficial in terms of predictive crew performance modeling,” Cateau said.

“Based on analyzing previous scenarios and previous outcomes, we can one day create models that will…provide the outcome before they run in simulators and provide feedback to the operational world with that, and…maybe update some of the SOPs or training or [aircraft] design.”

AI might also help mitigate operational drift, where pilots increasingly fly outside of specified parameters. Using the concept of unsupervised learning, the safety intelligence data is tapped for useful information. “You feed the machine with the data and you let it find patterns, trends, correlation between inputs,” he said.

“So data mining…if we have the infrastructure to look at that in a very comprehensive way, we can expect some findings on the operational drift. For example, it’s really hard for a human to capture, is there an operational drift or not? It's very hard to answer that question, but having a more comprehensive dataset and some AI algorithms we can expect in the future, maybe [there is] some additional capability towards reducing that drift.”