ORIGINAL RESEARCH article
Front. Artif. Intell.
Sec. AI in Business
Volume 8 - 2025 | doi: 10.3389/frai.2025.1565927
Understanding Acceptance and Resistance Toward Generative AI Technologies: A Multi-Theoretical Framework Integrating Functional, Risk, and Sociolegal Factors
Provisionally accepted
- Hult International Business School, London, United Kingdom
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To provide a more cohesive theoretical framework, this study integrates the Technology Acceptance Model (TAM), Protection Motivation Theory (PMT), and Social Exchange Theory (SET) to explain both acceptance and resistance toward generative AI among college students. Rather than treating these theories as separate constructs, this study highlights their interconnections and how they collectively shape user attitudes. TAM provides the foundation for understanding functional factors, emphasizing that perceived usefulness and ease of use drive acceptance. However, technology adoption is not solely determined by functionality-perceived risks also play a critical role. PMT complements TAM by introducing the concept of threat and coping appraisals, which explain resistance behavior. For instance, while TAM suggests that an easy-to-use and useful AI system should encourage adoption, PMT explains that if students perceive privacy risks, data security concerns, or ethical issues, they may resist the technology despite its functional benefits
Keywords: Technology adoption model, Protection Motivation Theory, Gen AI adoption, Social exchange theory (SET), Acceptance Resistance Framework
Received: 23 Jan 2025; Accepted: 07 Apr 2025.
Copyright: © 2025 Shrivastava. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Priyanka Shrivastava, Hult International Business School, London, United Kingdom
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