Reskilling for Agentic Ecosystems: Designing Education and Training for Human–AI Collaboration

The rapid emergence of agentic AI ecosystems comprising autonomous, goal-driven, and collaborative AI agents is reshaping the nature of work, decision-making, and human roles in digital environments. As organizations transition from traditional automation toward hybrid intelligence and human–AI teaming, reskilling has become a strategic imperative. This study investigates the competencies, pedagogical models, and training architectures required to prepare individuals for effective collaboration with autonomous AI agents. Through an integrative review of current literature, expert interviews, and analysis of emerging human–agent workflows, the research identifies critical skill domains including AI literacy, dynamic task delegation, trust calibration, oversight capability, and ethical reasoning. Findings highlight significant gaps in existing education and workforce development systems, particularly in areas related to co-agency, adaptive learning, and socio-technical problem solving. The study proposes a comprehensive reskilling framework designed to support human adaptability, enhance shared situational awareness, and enable effective participation in agentic ecosystems. This framework offers actionable guidance for educators, policymakers, and organizations seeking to develop resilient, AI-augmented workforces capable of thriving in rapidly evolving technological landscapes.