Readiness of HRM Departments in the Kingdom of Saudi Arabia to Integrate Artificial Intelligence Technologies into Their Practices

The aim of this study was to measure the readiness of these departments to apply artificial intelligence based on several variables that have been shown through the literature to have their impact on the application of artificial intelligence in human resources departments. In addition, the study aimed to identify the factors directly and indirectly affecting this application; as a first stage, qualitative data (theoretical framework and preliminary interviews) were collected and analyzed; the qualitative results were then used to build quantitative measurement tools for the study, where a targeted questionnaire was designed for managers of human resources departments and tested via a survey study. After confirming their validity, the data was collected and analyzed. The most important findings of the study were that there is an average readiness among government human resources departments in the Kingdom of Saudi Arabia to apply artificial intelligence, by measuring axes with specific indicators included in a questionnaire distributed to the managers of human resources departments in government agencies such as ministries, bodies, and others. Managers gave a high rating to the readiness of their departments with respect to certain application-level signals, digital leadership, and reliance on analytics, while giving an average rating of both infrastructure and regulations, and a low rating of both employees' digital skills and open organizational culture. By testing the path analysis, the study came up with a mathematical model that illustrates the relationships and mutual effects between variables on the application of artificial intelligence. The results of the analysis concluded that digital leadership, reliance on analytics, and infrastructure were all having a direct impact on the application of artificial intelligence. Employee skills and an open organizational culture have had an indirect impact on the application of AI