This study proposes a novel dual-framework model integrating the Technology Acceptance Model (TAM) with an AI Ethics Framework, introducing “Ethical Readiness” as a critical mediating construct for AI adoption in higher education. Using 2021 survey data from 47 educators, administrators, and policymakers across 26 countries, the research establishes a pre-generative AI baseline to analyse drivers, barriers, and solutions. Key drivers include data-informed decision-making, pedagogical personalisation, and administrative efficiency, aligning with TAM’s perceived usefulness and ease of use. Significant barriers are limited AI literacy, inadequate infrastructure, and unresolved ethical concerns, such as algorithmic bias and data privacy. Proposed solutions focus on ethical policy frameworks, capacity-building, and infrastructural investment. The findings gain urgent relevance in the post-generative AI era, where tools like ChatGPT have accelerated adoption while intensifying ethical and pedagogical challenges. The Ethical Readiness construct, defined as an institution’s systemic capacity to ensure transparent, fair, privacy-compliant, and accountable AI deployment, provides a forward-looking framework for navigating this evolving landscape. The study concludes that sustainable AI integration requires not only technological acceptance but also institutional ethical preparedness, bridging behavioural intention with normative accountability. This research offers a theoretically grounded, actionable paradigm for equitable and governance-aware AI implementation in Cross-Cultural higher education contexts.
Slimi et al. (Tue,) studied this question.
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