Trends in the Adoption of Artificial Intelligence in Knowledge Management: An Analytical Study Using the Technology Acceptance Model (TAM) in Saudi Organizations in Line with Vision 2030

Abstract

This study aimed to analyze the factors influencing the adoption of artificial intelligence (AI) in knowledge management within Saudi organizations, using the Technology Acceptance Model (TAM), Data were collected from 384 employees working in Saudi organizations that utilize AI technologies, using an electronic questionnaire based on a five-point Likert scale. The data were analyzed using multiple linear regression to examine the impact of independent variables (perceived ease of use, perceived usefulness, attitude toward use, and behavioral intention to use) on the actual adoption of AI.
The results revealed that attitude toward use (ATU) was the most influential factor in the actual adoption of AI, with a strong regression coefficient (β = 0.943, p < 0.001). Behavioral intention to use (BIU) also showed a positive impact (β = 0.287, p < 0.001), though it was weaker compared to ATU. On the other hand, perceived usefulness (PU) recorded an unexpected negative effect (β = -0.320, p < 0.001), while perceived ease of use (PEOU) did not show a statistically significant impact (β = 0.030, p = 0.324), These findings are attributed to the unique challenges in the Saudi context, such as the high cost of implementing AI systems and difficulties in integrating them with existing infrastructure. This study contributes to enhancing the understanding of technology adoption in emerging contexts and provides practical recommendations for decision-makers to support digital transformation in line with the goals of Saudi Vision 2030, including improving infrastructure and offering specialized training programs.