What question did this study set out to answer?

The aim is to investigate how artificial intelligence enhances knowledge management and organizational learning in Saudi educational institutions.

June 12, 2026Open Access

Artificial intelligence and knowledge management in Saudi Arabian educational institutions: A statistical analysis

Key Points

The aim is to investigate how artificial intelligence enhances knowledge management and organizational learning in Saudi educational institutions.
Descriptive-analytical approach
Stratified random sample of 213 faculty members from five universities
Data collected through a validated 20-item questionnaire measuring four dimensions
AI implementation in knowledge management reported at M = 3.89, SD = 0.67
AI significantly predicts organizational learning outcomes with β = 0.624, p ≤ 0.001, R² = 0.389
Implementation challenges moderated the AI-knowledge management relationship with β = -0.187, p = 0.008

Abstract

This study investigated the role of artificial intelligence (AI) in improving knowledge management and organizational learning within Saudi Arabian educational institutions, with particular emphasis on the empirical statistical validation of the relationships between AI implementation and organizational outcomes. A descriptive-analytical approach was employed utilizing a stratified random sample of 213 faculty members from five Saudi government universities: Taiba University, King Faisal University, King Khalid University, Al-Jouf University, and Qassim University. Data were collected through a validated 20-item questionnaire (α = 0.978) measuring four dimensions: AI implementation in knowledge management, AI's role in organizational learning, implementation challenges, and effectiveness. Statistical analyses included descriptive statistics, Pearson correlations, multiple regression analysis, one-way ANOVA, independent samples t-tests, and structural equation modeling to test the hypothesized relationships. The results revealed high levels of AI implementation in knowledge management (M = 3.89, SD = 0.67) and organizational learning (M = 3.79, SD = 0.75). Multiple regression analysis demonstrated that AI implementation significantly predicted organizational learning outcomes (β = 0.624, p 0.001, R² = 0.389). Significant differences in AI implementation effectiveness were found based on institutional affiliation (F(4,208) = 4.87, p = 0.001, η² = 0.086) and academic rank (F(3,209) = 3.42, p = 0.018, η² = 0.047). The primary challenges identified, lack of AI expertise (M = 3.64), staff resistance (M = 3.58), and infrastructure limitations (M = 3.55), were found to significantly moderate the relationship between AI and knowledge management (interaction effect: β = -0.187, p = 0.008). This study contributes robust empirical evidence to the limited body of quantitative research on AI integration in Saudi higher education, providing statistically validated insights for policymakers and institutional leaders working to advance Vision 2030 objectives.

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