AI in Aviation: From Passenger Experience to Predictive Operations

Artificial intelligence is reshaping aviation across the entire journey, from the moment a passenger plans a trip until the aircraft reaches its destination. But where is AI already creating real value, and what developments are coming next?

In this presentation, Newsha Ghoreishi travels around the world and explores how AI, machine learning, computer vision, digital twins and intelligent optimisation are transforming airports, airlines and air traffic management. The session will cover practical applications such as passenger-flow forecasting, personalised travel assistance, baggage tracking, crew and fleet planning, predictive maintenance, disruption management, aircraft turnaround optimisation, food-demand forecasting, flight-path optimisation and delay prediction.

Drawing on insights from international summits, conferences and industry demonstrations, Newsha will also introduce emerging software, AI systems, start-ups, initiatives and prototypes that signal where aviation technology is heading. The presentation will look beyond the enthusiasm surrounding AI and address the engineering questions that determine whether an AI solution can be trusted: data quality, explainability, validation, human oversight, cybersecurity, safety assurance and responsible implementation.

The audience will leave with a practical understanding of where AI is being used today, which applications are approaching operational maturity, and what engineers must consider when moving an AI solution from an exciting demonstration into dependable aviation operations.

Speaker Biography:

Newsha Ghoreishi, PhD, has more than 10 years of experience in aviation and two decades of experience in software engineering. Currently, she works as Test Manager for Aeronautical and AI-driven systems in Copenhagen Airport. Her career spans software development, quality assurance, test management and the validation of complex aeronautical systems.

She holds a PhD in Computational Intelligence, which has given her a deep technical understanding of complex systems, predictive modelling, machine learning and optimisation methods. By combining this foundation with extensive aviation experience, she brings a multidisciplinary perspective to how intelligent technologies can be developed, tested and introduced into operational environments.

In 2026, she was recognised as one of Denmark’s Top 100 Women in AI and among the top 10 in the Data & Intelligence category.