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This study investigates the primary technological and socio-environmental factors influencing the adoption intentions of AI-powered technology at the corporate level within higher education institutions. A conceptual model based on the Diffusion of Innovation Theory (DOI), the Technology–Organization–Environment (TOE), and the Technology Acceptance Model (TAM) combined framework were proposed and tested using data collected from 367 higher education students, faculty members, and employees. SPSS Amos 24 was used for CB-SEM to choose the best-fitting model, which proved more efficient than traditional multiple regression analysis to examine the relationships among the proposed constructs, ensuring model fit and statistical robustness. The findings reveal that Compatibility “C”, Complexity “CX”, User Interface “UX”, Perceived Ease of Use “PEOU”, User Satisfaction “US”, Performance Expectation “PE”, Artificial intelligence “AI” introducing new tools “AINT”, AI Strategic Alignment “AIS”, Availability of Resources “AVR”, Technological Support “TS”, and Facilitating Conditions “FC” significantly impact AI adoption intentions. At the same time, Competitive Pressure “COP” and Government Regulations “GOR” do not. Demographic factors, including major and years of experience, moderated these associations, and there were large differences across educational backgrounds and experience.
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Stored only when both papers are in the corpus — 36 citations exist upstream.
Papers that cite the same references — the relational fallback while embeddings are still backfilling.
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