Paper Type

Short

Paper Number

PACIS2026-1312

Description

As Artificial Intelligence evolves into autonomous agents, understanding how agent autonomy impacts team performance by reshaping social hierarchies is critical. This study conducted a code development field experiment spanning 160 team-weeks, combining mixed-effects modeling of varied autonomy modes with qualitative interaction log analysis. Results reveal a dual-pathway mechanism: heightened agent autonomy enhances performance by establishing expert power. Conversely, it elevates agent social status, inducing human blind compliance and reduced engagement, yielding a negative masking effect. Theoretically, this research disentangles expert power from social status, extending social hierarchy logic to human-AI hybrid teams. Practically, organizations must balance agents' professional empowerment with mitigating human cognitive inertia by embedding ultimate gatekeeping responsibilities into workflows.

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Jul 5th, 12:00 AM

From Passive Tools to Autonomous Teammates: How Agent Reshapes Team Performance through Social Hierarchy Restructuring

As Artificial Intelligence evolves into autonomous agents, understanding how agent autonomy impacts team performance by reshaping social hierarchies is critical. This study conducted a code development field experiment spanning 160 team-weeks, combining mixed-effects modeling of varied autonomy modes with qualitative interaction log analysis. Results reveal a dual-pathway mechanism: heightened agent autonomy enhances performance by establishing expert power. Conversely, it elevates agent social status, inducing human blind compliance and reduced engagement, yielding a negative masking effect. Theoretically, this research disentangles expert power from social status, extending social hierarchy logic to human-AI hybrid teams. Practically, organizations must balance agents' professional empowerment with mitigating human cognitive inertia by embedding ultimate gatekeeping responsibilities into workflows.