(untitled) (International Journal of Financial, Administrative and Economic Sciences, 2025)
This research aims to examine the readiness of Saudi organizations to adopt artificial intelligence technologies in project management, in light of the accelerating digital transformation led by Saudi Vision 2030. The study adopted a rigorous quantitative approach, including verifying the validity and reliability of the study tool using Cronbach’s alpha coefficient and structural validity analysis. Data were also analyzed using descriptive statistics, correlation and multiple regression analyses, and group difference tests. The sample included 114 valid responses, distributed between the government sector (52.6%) and the private sector (47.4%), with a roughly balanced representation of small (29.8%), medium (40.4%), and large (29.8%) organizations. The data also showed that 50% of participants had between 5 and 10 years of professional project management experience. Descriptive results revealed that the overall level of readiness of organizations fell within the "average to good" range, with an average technical readiness score of 3.80, organizational readiness of 3.77, and cultural readiness of 3.80. The average actual adoption of AI in project management was 3.68. Key technical strengths included advanced cloud infrastructure (4.12) and effective mechanisms for encrypting sensitive data (4.05). However, some technical gaps emerged that require improvement, such as the inefficiency of high-speed communication networks (3.65), poor ongoing technical support services (3.76), and challenges in integrating systems with AI interfaces (3.79). Results from correlation and multiple regression analyses confirmed a positive and statistically significant relationship between all readiness dimensions (technical, organizational, and cultural) and the level of AI adoption. The results showed that cultural readiness was the most influential predictor of adoption (beta coefficient = 0.34, p < 0.001), followed by technical readiness (beta = 0.28), and then organizational readiness (beta = 0.21). The statistical model explained 52% of the variance in adoption. Regarding the difference tests, the results showed no statistically significant differences in the level of adoption between government and private institutions (p = 0.27), nor between institutions of different sizes (p = 0.09), indicating that the challenges and opportunities are largely similar across different sectors. This study provides an important scientific and applied basis for decision-makers in the public and private sectors, emphasizing the importance of balancing technical, organizational, and cultural readiness, while highlighting the critical role of corporate culture in enhancing organizations’ ability to adopt AI in project management, thus supporting national digital transformation efforts.