<![CDATA[Objective: This article focused on developing a causal model of the causes and effects relating to the impact of artificial intelligence on human resource development in public hospitals in Iraq, with the aim of identifying and prioritising the key influencing factors and outcomes associated with this technology, and analysing them. Method: This study is considered applied research in terms of its purpose and employed a mixed-methods approach (qualitative-quantitative). In the qualitative phase, the fuzzy Delphi method was used, involving 11 experts, including senior managers, human resource specialists and information technology specialists from public hospitals in Iraq, over three iterative rounds. The cause-and-effect factors of AI’s impact were identified through a systematic review of the literature and expert opinions. Data were analysed using fuzzy triangular means (a, b, c), non-fuzzy numerical values, and Kendall’s coefficient to assess consensus among experts and determine the final priority of factors. Results: The results revealed that, among the antecedent factors, ‘technological infrastructure and integration’, ‘human factors and readiness (organisational acceptance)’ and ‘organisational structure and operational factors’ ranked highest. With regard to the subsequent factors, ‘Reduction in HR costs and financial results’, ‘Process automation’ and ‘Improvement of the employee experience and reduction of discrimination’ occupied the top three positions. Other factors, such as ‘performance evaluation’, ‘improved productivity’, ‘staff retention’ and ‘improved management’ ranked in the mid-range. The study concluded that the use of artificial intelligence for human resource development in public hospitals in Iraq requires a two-pronged approach: Firstly, ensuring that technological and organisational requirements are in place, including suitable infrastructure, integration of technologies and workforce readiness; and secondly, managing the outcomes of AI implementation, particularly in reducing costs, automating processes and enhancing the employee experience. Novelty: This study is considered applied research in terms of its purpose and employed a mixed-methods approach (qualitative-quantitative). In the qualitative phase, the fuzzy Delphi method was used, involving 11 experts over three iterative rounds, and the cause-and-effect factors of AI’s impact were identified through a systematic review of the literature and expert opinions.]]>
