Objective
One of the fundamental challenges in the adoption of artificial intelligence within organizations is not merely the accessibility of advanced technologies or tools, but rather the actual readiness of users, managers, and organizational structures to accept and effectively utilize such technology. In many instances, despite considerable investment in emerging technologies, organizations encounter serious difficulties in achieving successful implementation due to an insufficient understanding of the prerequisites, requirements, and key factors that influence organizational readiness. This issue carries particular significance in the domain of human resource management, as its processes are directly intertwined with personnel, sensitive data, managerial decision-making, and ethical considerations. Consequently, the present study was conducted with the objective of identifying and prioritizing the key factors of organizational readiness for the application of artificial intelligence in human resource processes, thereby providing managers and decision-makers with a clear and structured understanding of the most critical prerequisites for the successful deployment of this technology.
Methods
In terms of its overarching purpose, this study qualifies as applied research, as it seeks not only to expand the existing body of knowledge but also to offer practical, actionable guidance for organizations intending to implement artificial intelligence in human resource management. The research was carried out in two distinct stages. In the first stage, a systematic review of the extant literature was undertaken to identify the initial factors affecting organizational readiness. This stage was designed to collect, analyze, and synthesize the findings of previous empirical and theoretical studies, with the aim of extracting the most salient dimensions and indicators relevant to organizational readiness for AI adoption. Subsequently, the Best-Worst Method, a well-established multi-criteria decision-making approach, was employed to prioritize the identified factors. This method is widely recognized as a reliable and robust technique in decision analysis, as it facilitates a more precise and consistent ranking of factors based on expert judgment. The statistical population of the study comprised 15 employees and specialists with expertise in human resources, smart human resource management, and transformative technologies. These individuals were selected as the primary source of expert judgment due to their specialized familiarity with the subject matter and their direct engagement with the relevant organizational and technological contexts.
Results
The findings of the study revealed that organizational readiness for the application of artificial intelligence in human resource processes is inherently multidimensional in nature and is shaped by a total of 12 key factors. Among these, managerial readiness emerged as the most influential and significant factor. This component encompasses the commitment, support, and active participation of senior managers throughout the process of adopting and implementing artificial intelligence. The pronounced importance of this factor underscores the reality that, in the absence of genuine managerial backing, including adequate resource allocation, proactive mitigation of organizational resistance, and effective steering of necessary structural and cultural changes, the implementation of AI technologies is unlikely to achieve success. Indeed, top management plays a pivotal role in fostering motivation, defining strategic priorities, and guiding the organization toward the acceptance and integration of innovation. Following managerial readiness in order of priority, strategic readiness and workforce readiness were identified as the next most critical factors. Strategic readiness emphasizes the necessity of aligning AI-related goals and programs with the broader overarching strategies of the organization. This finding indicates that the use of artificial intelligence should not be pursued in an isolated, fragmented, or purely technology-driven manner; rather, it must be situated within a clear and coherent roadmap that is fully aligned with organizational objectives. On the other hand, workforce readiness highlights the essential requirement for employees and HR specialists to possess the requisite knowledge, skills, and capabilities to interact effectively with AI tools. The findings suggest that higher levels of digital literacy, analytical proficiency, and general readiness for continuous learning among employees are positively associated with a greater likelihood of success in the application of this technology.
Conclusion
The results of the study collectively demonstrate that the successful adoption and effective application of artificial intelligence in human resource management depend, more than anything else, on a range of internal organizational factors. Managerial commitment and sustained support, the formulation of clear and coherent strategies, the systematic development of workforce skills and competencies, the strengthening of technological infrastructure and capabilities, and the improvement of data quality and governance mechanisms are all identified as the most important prerequisites for success in this domain. Although institutional, legal, and environmental factors also exert some influence on the AI adoption process, their overall impact appears to be comparatively less significant than that of managerial, strategic, and human-centric factors. These findings offer practical and actionable guidance for human resource managers in planning their AI adoption strategies, prioritizing their investments, and effectively implementing AI-based technologies within their organizations.