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This research conducts a comprehensive investigation into the impact of Artificial Intelligence (AI) on the educational landscape of the Kingdom of Saudi Arabia (KSA). Utilizing well-established theoretical frameworks such as the Theory of Planned Behaviour (TPB), Unified Theory of Acceptance and Use of Technology (UTAUT), and Technology Acceptance Model (TAM), the study employs primary data collected through a survey involving 198 participants, including students, faculty/teachers, and administrators in educational institutions. Data analysis, carried out using Eviews software, focuses on understanding the readiness for AI adoption in the educational context of KSA. The research addresses the absence of a comprehensive theoretical framework for guiding effective AI application in education. The survey, conducted through stratified random sampling, provides insights into participants' demographics and attitudes toward AI adoption. Findings reveal that approximately 35-40% of respondents expressing favourable attitudes, indicating the need for further exploration and educational initiatives. Regression analyses underscore the significance of factors such as attitude, knowledge, and usefulness in predicting AI adoption intention, demonstrating variations across gender, age groups, and professional roles. To address identified gaps, the study introduces an innovative AI Readiness Assessment Tool, designed based on TPB, UTAUT, and TAM frameworks. This tool evaluates individuals' preparedness for AI integration and provides a comprehensive assessment. The research proposes operational strategies and guidelines tailored for students, faculty, and administrators to enhance AI adoption in educational institutions. In conclusion, this research contributes a foundational theory for understanding AI's role in education in KSA, providing valuable insights and practical recommendations for educators, policymakers, and technologists. The study lays the groundwork for a modern, adaptive, and effective educational future aligned with the goals of Vision 2030.
Musawa et al. (Mon,) studied this question.