Integrating the Literature on AI Adoption: A Socio-Technical Framework
Year: 2025
Type: article
Study design: Systematic Review
Abstract: This paper develops an integrative framework for consumer AI adoption that addresses the complex interactions between AI technologies, consumer behaviors, and socio-cultural contexts. Through a systematic literature review of 243 seminal studies, we conducted a three-step analysis. First, we used content analysis to clarify AI adoption conceptualizations and map the existing literature. Second, we employed thematic analysis to inductively categorize antecedents and develop a conceptual framework, which emerged to align with socio-technical systems theory. Third, we conducted a cross-tabulation analysis to examine how antecedents vary across different AI technologies. Our findings reveal significant diversity and complexity in AI adoption patterns. Based on this, we propose an integrative framework encompassing AI-related, consumer-related, and AI-consumer interaction-related antecedents, grounded in socio-technical theory. This framework accommodates unique features of specific AI technologies in providing practical guidance for researchers and practitioners.
Authors: Kathleen Desveaud, Ransome Bawack
Institutions: Kedge Business School, Audencia Business School
Language: English
Subfield: Information Systems and Management
Field: Decision Sciences
Domain: Social Sciences
Open Access status: green
OpenAlex ID: W4414649498