Document Type : Research Article
Authors
1 PH.D student, Faculty of Economics, Management and Administrative Sciences, Semnan University, Semnan, Iran
2 Professor, Faculty of Economics, Management and Administrative Sciences, semnan university
3 Professor Faculty of Economics management and administrative sciences, Semnan university, Semnan, Iran
Abstract
Purpose: This article aims to examine the impact of Artificial Intelligence (AI)-augmented Human Resource Management (HRM) on employee flourishing in organizations. In this research, the role of AI in enhancing employee satisfaction, motivation, and commitment is outlined by identifying key indicators and analyzing causal relationships among them.
Design/ methodology/ approach: This research adopts a descriptive-analytical and mixed-methods (qualitative-quantitative) approach. Initially, in the qualitative phase, key indicators of AI-augmented HRM were extracted using text mining and web-based tools, such as Voyant and RapidMiner. Then, the causal relationships between these indicators and employee flourishing were analyzed using the fuzzy DEMATEL method in Excel. Data were collected from expert opinions and reputable international articles published between 2013 and 2024.
Research Findings: AI-augmented HRM plays a pivotal and effective role in enhancing employee flourishing. “AI-augmented planning” was recognized as the most influential factor in improving growth opportunities, career development, and employee satisfaction. Meanwhile, “AI-augmented leadership” had the greatest impact among the indicators, highlighting the critical role of leadership in the successful implementation of smart technologies and in motivating human resources. Additionally, the indicators “strategy” and “AI-augmented control” were identified as causal and decisive factors in the structure of intelligent HRM, with their improvement leading to optimized processes and increased employee commitment. These results emphasize the importance of a systematic, comprehensive approach to leveraging AI in HRM and demonstrate that achieving employee flourishing requires integrating AI with ethical frameworks, transparency, and active human participation to maintain organizational trust and fairness.
Limitations & Consequences: Despite presenting a comprehensive framework and detailed analysis of causal relationships among AI-augmented HRM indicators, this study has limitations. First, the focus on Iranian organizations and the limited number of experts may limit the generalizability of the findings to other cultures and industries. Moreover, the lack of in-depth investigation into the effects of other cultural, structural, and environmental factors on employee flourishing is another limitation. These limitations imply that future research should be conducted across diverse organizational environments, using broader, multi-source data, and should further explore the ethical, social, and long-term impacts of AI in HRM through interdisciplinary approaches.
Practical Consequences: The findings offer significant practical implications for managers and organizations, including that the intelligent use of AI technologies in HR planning and leadership can improve decision-making processes, enhance job satisfaction, and increase employee motivation and commitment. Organizations should invest in training and empowering employees in digital and AI skills while ensuring the application of ethical frameworks and transparency in implementing these technologies to preserve organizational trust and fairness. Furthermore, strengthening an organizational culture that embraces innovation and fosters constructive human-machine interaction can lead to greater productivity and sustainable employee flourishing in smart work environments.
Innovation or value of the Article: This article provides an innovative interdisciplinary framework combining text mining and fuzzy DEMATEL analysis to investigate the role of AI in HRM and employee flourishing—an approach that has rarely been used in existing literature. Moreover, integrating the Harvard Model and Ulrich’s HR roles framework to analyze causal relationships adds significant theoretical value and provides a comprehensive, strategic, and ethical framework for leveraging AI in HRM. As such, this research plays a pioneering role in advancing both practical and theoretical knowledge in the field of intelligent HRM.
Paper Type: Original Paper
Keywords