Abstract: Agentic AI systems pursue goals, make decisions and act with minimal human intervention, distinguishing them from the traditional technologies organizations have adopted to date. This study identifies the antecedents of agentic AI adoption in workplace settings through a systematic literature review from the Scopus and Web of Science databases. From 418 records, 21 primary studies on agentic AI adoption were identified, yielding 30 consolidated antecedents. Organizational antecedents were mapped to the Technology–Organization–Environment framework, while individual antecedents were grouped as agent-related, user-related and work-related. Technical infrastructure and organizational readiness were the most frequently reported organizational antecedents, whereas AI experience and perceived autonomy were reported most frequently at the individual level. Perceived autonomy emerges as the construct that most clearly distinguishes agentic AI, and the evidence indicates it acts in two directions at once. The review contributes a consolidated antecedent taxonomy spanning both individual and organizational levels of adoption.

Keywords: Agentic AI, Technology Adoption, Systematic Literature Review, Antecedent Taxonomy, TOE Framework.