Integrating the Literature on AI Adoption: A Socio-Technical Framework

Kathleen Desveaud and Ransome Bawack ()
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Kathleen Desveaud: Kedge BS - Kedge Business School
Ransome Bawack: Audencia Business School

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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 threestep 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 AIrelated, consumer-related, and AI-consumer interaction related antecedents, grounded in sociotechnical theory. This framework accommodates unique features of specific AI technologies in providing practical guidance for researchers and practitioners.

Keywords: artificial intelligence; AI adoption; systematic review; socio-technical systems theory; consumer (search for similar items in EconPapers)
Date: 2026-03
Note: View the original document on HAL open archive server: https://hal.science/hal-05608836v1
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Published in International Journal of Market Research, 2026, 68 (2), pp.219-240. ⟨10.1177/14707853251383383⟩

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Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:hal-05608836

DOI: 10.1177/14707853251383383

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