Understanding human roles in AI-driven aviation through an evolutionary economics lens

Abstract

This study investigates how human roles retain strategic value in AI-driven aviation through an evolutionary economics lens. Using a mixed-methods approach – combining theoretical analysis, case studies, a Delphi process, and scenario forecasting – the paper reveals co-evolutionary dynamics where innovation and institutional selection drive workforce adaptation in aviation. Findings indicate that human roles evolve toward strategic oversight (e.g., ethical judgment, crisis management) and hybrid skill sets (e.g., AI supervisors, predictive maintenance), with the “AI-augmented workforce” emerging as the most plausible future in 2040. Key factors in achieving this balance include regulatory agility, workforce adaptability, and trust-building. The study pioneers the application of evolutionary economics to AI in aviation, offering a multidisciplinary framework to align technological advancements with socio-institutional realities. Practical recommendations include adaptive certification processes, hybrid training models, and ethical governance frameworks, positioning aviation as a model for human-AI collaboration in high-stakes industries.