Adaptive Agentic AI for Enhanced Human-Machine Teaming in Complex Operations

This paper presents a novel framework for integrating adaptive agentic AI systems into human-machine teams, focusing on dynamic task allocation, context-aware decision-making, and real-time learning. We demonstrate significant improvements in operational efficiency and error reduction in simulated complex scenarios such as disaster response and air traffic control. The AI agents are designed to understand human intent and adapt their autonomy levels to optimize team performance and ensure robust collaboration.