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Understanding AI adoption through expert discourse: A UTAUT-based analysis on LinkedIn
Ali Yari1, Mohammad Taghi Taghavifard1, Iman Raeesi Vanani1
1Department of Operations Management and Information Technology, Allameh Tabataba'i University, Tehran, Iran.
Plos One
|April 16, 2026
Summary
Technology experts
Area of Science:
- Artificial Intelligence (AI) and Technology Adoption
Background:
- The collective voice of AI technology experts on social networks remains largely unmapped.
- Understanding expert perspectives is crucial for navigating AI development and adoption.
Purpose of the Study:
- To decode the values and motivations of AI builders regarding technology adoption.
- To re-contextualize the Unified Theory of Acceptance and Use of Technology (UTAUT) for AI experts.
Main Methods:
- Analysis of tens of thousands of AI-related LinkedIn posts.
- Application of an embedding-based topic-modeling pipeline.
- Integration with the Unified Theory of Acceptance and Use of Technology (UTAUT).
Main Results:
- AI experts redefine UTAUT constructs: Performance Expectancy (PE) as transformative breakthroughs, Effort Expectancy (EE) as cognitive efficiency, Social Influence (SI) as a dual role, and Facilitating Conditions (FCs) as an ecosystem.
- Cultural context significantly influences the interpretation of these constructs.
- A re-contextualized UTAUT model for AI adoption was proposed.
Conclusions:
- AI adoption is a complex negotiation for experts, not a one-size-fits-all scenario.
- Findings offer actionable insights for leaders in AI innovation.
- The study highlights the need for culturally sensitive models in understanding global AI uptake.
