AI in Aerospace, fiction or reality?

In the last International Aerospace and Innovation Forum, Siegfried Usal from Thales took part in a panel questioning AI in Aerospace: “Fiction or Reality?”.

If you missed this exchange, we summarized 4 key points of their discussion below.

AeroMontreal workshop with Ghislain Gagné (McKinsey & Company), Matt Holvey (Bell Textron), Jack Klejka (IVADO Labs), Sitaram Ram (Collins Aerospace), Rémi Duquette (Maya HTT) and Siegfried Usal (Thales)

#1 — An existing reality in the sector

The answer to the panel’s theme is clear: AI is already contributing to the Aerospace Industry as we speak. For numerous non-safety relevant applications, AI and Machine Learning prove their benefits in areas such as:

  • Revenue management for the airlines
  • Workflow and traffic optimization for Air Traffic Management and Air Navigation Service Provider (ANSP)
  • Predictive maintenance for Air-framers
  • Fuel efficiencies
  • Fraud detection for Airport or end-to-end passenger journey for Airlines and Airports.

As the industry is facing a capacity shortage and soaring demand, AI could play an essential role in revenue optimization and sustainability improvements.

#2 — AI and sustainability

Talking about sustainability, it is one of the targeted benefits of these existing AI applications. For example, Thales offered AI models for fuel optimization and derived solutions to help achieve zero carbon emission goals by 2050, transforming the just-in-time supply chain, and addressing labour shortages through increased automation. Learn more about Thales use cases in Eurocontrol’s Fly AI Report.

#3 — Acknowledging and tackling AI risks

As AI systems become more powerful, regulatory entities are paving the way toward Trustworthy AI. For example, the European Commission is giving industries Ethic Guidelines with three components to meet throughout the system’s entire life cycle:

  • Lawful AI, complying with all applicable laws and regulations,
  • Ethical AI, ensuring adherence to ethical principles and values,
  • Robust AI, both from a technical and social perspective, since, even with good intentions, AI systems can cause unintentional harm.

#4 — AI for safety-critical applications

Trustworthy AI is necessary to drive safety-critical applications. Adding to the European guidelines, the European Union of Aviation Safety Agency (EASA) worked with companies, including Thales, to build an AI Roadmap with a human-centric approach.

From Air Traffic Management to drones’ autonomy or systems for Safety Risk Management, AI can bring positive impacts spanning all industry verticals.

Learn more about our human-centric approach for AI in critical missions in the latest episodes of our 8-minute podcast episodes.



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