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Abstract AI Communication Technologies (AICTs) make decisions about users’ communication on their behalf. Users’ implementation of AICTs that autonomously act may enable and constrain how they accomplish their work and interact with others. Drawing on interviews with users of two AICTs with differing levels of autonomy designed for work-related scheduling, this study investigated how users enacted AICTs in practice. Users of both tools drew on AICTs’ autonomous capabilities to enact machine agency, a structure that assigns AICTs the power to allocate resources, which helped them increase scheduling efficiency and guide how others interacted with them. Users of the tool that autonomously implemented decisions described a process of enactment in which they used the tool to control their work, perceived the tool was exhibiting too much control, and acted to regain control. I present implications for understanding how people enact machine agency with AICTs that make decisions about their work. 

Abstract Artificially intelligent communication technologies (AICTs) that operate autonomously with high degrees of conversational fluency can make communication decisions on behalf of their principal users and communicate with those principals’ audiences on their behalf. In this study, we explore how the involvement of AICTs in communication activities shapes how principals engage in impression management and how their communication partners form impressions of them. Through an inductive, comparative field study of users of two AI scheduling technologies, we uncover three communicative practices through which principals engaged in impression management when AICTs communicate on their behalf: interpretation, diplomacy, and staging politeness. We also uncover three processes through which communication partners formed impressions of principals when communicating with them via AICTs: confirmation, transference, and compartmentalization. We show that communication partners can transfer impressions of AICTs to principals themselves and outline the conditions under which such transference is and is not likely. We discuss the implications of these findings for the study of technological mediation of impression management and formation in the age of artificial intelligence and present propositions to guide future empirical research.