Visioning Human-Agentic AI Teaming: Continuity, Tension, and Future Research

This academic research paper examines the challenges of human-AI teaming as AI systems become more autonomous and agentic. The study proposes extending Team Situation Awareness theory to address structural uncertainties that arise when AI systems can take open-ended actions and evolve their objectives over time.

• →Agentic AI systems introduce structural uncertainty into human-AI collaboration through unpredictable behavior trajectories and evolving objectives.
• →Traditional alignment methods based on bounded outputs are insufficient for dynamic AI systems that continuously generate and revise plans.
• →Team Situation Awareness theory needs extension to handle the complexities of open-ended AI agency and heterogeneous system coordination.
• →The core challenge is maintaining alignment between humans and AI as both continuously adapt rather than achieving momentary agreement.
• →Future research must distinguish between areas where foundational teaming insights remain valid versus where new approaches are needed.