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February 16, 20260 citationsOpen Access

Co-Agency of AI, A Literature Review on Theorizing Al as institutional actors.

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GTGerin Trautenberger

Key Points

  • This review aims to theorize artificial intelligence as institutional actors and their integration into organizational fields.
  • Conducted an AI-assisted discovery and screening workflow for literature.
  • Identified 1,093 candidate publications and narrowed them to 50 high-relevance papers.
  • Analyzed scholarship across media, management research, sociology, law, public governance, and higher education.
  • AI is recognized as capable of shaping authority and decision-making within organizations.
  • Most studies focus on institutional responses to AI rather than its role as a rule-maker.
  • Conceptual fragmentation and lack of empirical evidence about AI’s agency as members in institutions are highlighted.

Abstract

This literature review examines how contemporary scholarship theorizes artificial intelligence as an institutional actor, focusing on whether and how AI systems gain legitimacy, authority, and norm-shaping capacity within organizational and societal fields. Drawing on an AI-assisted discovery and screening workflow, the review identifies 1,093 candidate publications and narrows them to 50 high-relevance papers spanning media and journalism studies, organizational and management research, sociology, law, public governance, and higher education. The synthesis shows broad recognition that algorithms can function institutionally by structuring behavior and decision-making, yet the field remains conceptually fragmented and empirically underdeveloped. Most empirical studies analyze institutional adaptation and governance responses to AI rather than tracing processes through which AI systems themselves become embedded as durable rule-makers. The most promising advances come from sociotechnical and distributed-agency approaches, including actor-network theory and hybrid human–algorithm configurations, but these frameworks often leave ontological questions of “actorhood” unresolved. The review concludes that a mature, evidence-based theory of AI as institutional actors is still lacking, and it outlines priority research directions for empirically studying legitimation, institutionalization indicators, and cross-disciplinary integration.

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Cite This Study

Gerin Trautenberger (2026) studied this question.

synapsesocial.com/papers/6992652ceb1f82dc367a1168https://doi.org/10.5281/zenodo.18643433
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