Orchestrating human-AI hybrids: Agency formation and re-configuration through conversational AI agents in physical service environments

Abstract

Abstract Despite the proliferation of agentic technologies in service systems, empirical research on bridging AI agents into physical settings remains scarce. This study examines the integration of conversational AI agents as dynamic touchpoints within physical service environments, exploring how one or more human actors form and renegotiate agency configurations with these non-human agents. The study conducts an in-depth single-case study within a garden center retail setting, comprising observations and condensed semi-structured interviews with 83 customers across 42 interactions. Our qualitative analysis develops a framework that explains how agency configurations are shaped by 20 attributes across the stages of agency formation and iterative agency re-configuration. Agency formation emerges as an evaluation of attributes such as AI agent role and value, shaped by social dynamics and contextual factors. Agency re-configuration is triggered by information exchange and situational contingencies and facilitated by the availability of instructive mechanisms and loop learning. The findings advance understanding of value co-creation in physical service environments involving AI agents, highlighting levers for orchestrating effective agency configurations and addressing tensions between human agency and AI agency in polyadic human-AI hybrids.