Agentic Flight Intelligence: A Cognitive-Adaptive Architecture for Personalized Human–AI Teaming in Next-Generation Flight Decks

Modern flight decks are evolving from rule-based automation toward intelligent human–AI collaboration. This paper proposes Agentic Flight Intelligence (AFI), a conceptual cognitive-adaptive architecture that integrates cognitive digital twins, context awareness, intent prediction, agentic reasoning, trust calibration, adaptive explainable AI, safety governance, and continuous learning to support pilots during safety-critical flight operations. The manuscript synthesizes recent literature from artificial intelligence, aviation human factors, explainable AI, and human–AI teaming to identify existing research gaps and proposes a unified systems architecture together with a simulation-based evaluation methodology. This work is presented as a conceptual research framework intended to guide future implementation and experimental validation.