THE SILENT COWORKER: EXPLORING THE IMPACT OF AGENTIC AI ON TEAM DYNAMICS AND PRODUCTIVITY
DOI:
https://doi.org/10.35631/IJEMP.935066Keywords:
Agentic AI, Human-AI Collaboration, Human-AI Teaming, Silent Coworker Perspective, Team Dynamics, Team ProductivityAbstract
The emergence of Agentic Artificial Intelligence (AI) is reshaping organizational work by introducing autonomous and adaptive systems capable of participating in collaborative activities traditionally performed by human employees. Although human-AI research addresses trust, control, and teamwork, the mechanisms linking background AI activity to collective productivity require further specification. Using human-AI teaming as its main theoretical foundation, with Role Theory and socio-technical reasoning as supporting perspectives, this conceptual paper proposes the "Silent Coworker Perspective" to conceptualize AI that operates autonomously in the background, influencing coordination, decisions, communication, and task allocation without conventional human team membership. Through a synthesis of recent literature on human-AI collaboration, autonomy, trust, and team cognition, this study develops a conceptual framework illustrating how Agentic AI characteristics, including autonomy, adaptability, learning capability, and generativity, may shape human-AI relationship quality, which may subsequently affect team dynamics and team productivity. The framework extends human-AI teaming by distinguishing functional participation from explicit recognition as a teammate and proposing relationship quality and team dynamics as sequential mediators of productivity. The quasi-team member is a conceptual positioning, and the proposed relationships require empirical testing. The study concludes by offering theoretical implications, managerial recommendations, and future research directions for organizations integrating Agentic AI into collaborative work environments.
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