Working with Agentic `Teammates': When a New Organizational Actor Collides with the Human Ecosystem of Work

2026-09-24

AI Summary

This study addresses the lack of empirical understanding regarding human-AI collaboration boundaries and trust reconstruction mechanisms during the transition of enterprise AI toward proactive, multi-user agents. Employing qualitative field research within a large technology company, we examine the deployment of persistent, proactive AI teammates and integrate organizational behavior analysis to identify early micro-negotiation signals. Our findings reveal implicit rule conflicts, blurred relational boundaries, and agency redistribution, elucidating the dynamic evolution of human-AI work boundaries. Furthermore, this work proposes a novel research and design agenda that deliberately preserves human agency within shared workspaces, offering both theoretical foundations and practical guidelines for constructing intelligent collaborative systems that respect human subjectivity.

Abstract

Enterprise AI is transitioning from single-user, reactive tools toward proactive, multi-user 'teammates,' but our empirical understanding of this transition is limited. In this paper, we present an in-situ qualitative study of a persistent, proactive AI agent 'teammate' deployed across multiple teams in a large technology company. Our findings reveal the boundaries of the human-agent workplace are actively in flux, triggering breakdowns and negotiations across: 1) tacit rules of collaborative human workflows, 2) the relational boundaries of this new non-human actor, and 3) the redistribution of trust and human agency. We use these early micro-negotiations as signals to chart a new research, design, and organizational agenda that intentionally preserves human agency in a workplace shared with non-human organizational actors.

Problem

• Agentic AI teammates
• Human-AI collaboration
• Enterprise AI
• Human agency
• Organizational dynamics

Innovation

• Agentic AI
• Human-AI Collaboration
• In-situ Qualitative Study
• Human Agency
• Enterprise AI