Why Artificial Intelligence Challenges the Foundations of Technology Acceptance Models

Despite decades of refinement, technology acceptance models such as the Technology Acceptance Model (TAM; Davis, 1985, 1989) and the Unified Theory of Acceptance and Use of Technology (UTAUT; Venkatesh et al. 2003) remain the dominant frameworks for evaluating digital technologies. Their resilience reflects robustness and parsimony. Yet Artificial Intelligence (AI) changes the game. Unlike earlier systems, AI learns, adapts and acts, increasingly participating in the decisions, challenging the very assumptions on which TAM/UTAUT rest. As Venkatesh himself admitted, the acceptance of AI tools remains “a question mark”, raising doubts on the adequacy of established models (Venkatesh 2022). Drawing on a semi-systematic literature review (12,048 publications from 1985 to 2025, including 155 focused on AI acceptance), we show that while TAM/UTAUT still account for nearly 70% of studies, the field has entered a phase of conceptual displacement. Three converging dynamics stand out: an affective and experiential turn, a vulnerability-centered perspective and a socio-technical orientation. Together, they crystallize into three new research streams: trust-centered, adoption-oriented and ethics-centered, that shift the field away from individual-utilitarian framings toward relational, organizational and governance logics. The challenge ahead is clear: to decide whether constructs such as trust, affect, privacy, ethics and anthropomorphism are merely contextual moderators or the building blocks of a new paradigm. The age of AI calls for more than incremental refinements, it demands a shared theoretical framework capable of steering organizations and societies through both the promises and risks of intelligent systems.