Aug 2026· Person-centered review· pp. 1-24· 0 citations· 129 references
TL;DR
The article highlights that the integration of AI is revolutionizing TM by improving the methods used to identify, develop and retain talent and highlights the role of TM in pioneering managerial responses to AI integration to maximize organizational effectiveness.
Abstract
This article explores how both organizations and “talents” (talented employees) are responding to the adaptation of artificial intelligence (AI).
We follow a phenomenon-based approach to describe the key trends and challenges influenced by the new work arrangements and seek to address the who, how, where and why issues. Specifically, we discuss the impact of organizations' digital transformation on talent identification, and show how these changes configure new management challenges from a talent management (TM) perspective.
Our research highlights how AI is impacting people and organizations everywhere as the technology continues to advance, whereas the introduction of AI in the workplace is fundamentally changing existing work arrangements.
Our article examines how the TM agenda evolves as organizations adopt AI and highlights the role that employees play in the implementation of AI in the workplace–new developments that are recently neglected in the literature. The article highlights that the integration of AI is revolutionizing TM by improving the methods used to identify, develop and retain talent and highlights the role of TM in pioneering managerial responses to AI integration to maximize organizational effectiveness. The article enriches the literature by adding new research perspectives which enhance our understanding of how AI is reshaping TM agenda.
The integration of AI in Talent Management is a change in the way that organizations are designing their strategies for Talent Retention (TR), engagement, and future strategy. New and innovative tools such as predictive models, sentiment analysis, and personalized career planning have come up, and they offer better ways of addressing retention issues, workforce engagement, and, in general, sustainability. Through the application of predictive analytics, organizations can determine employees'likelihood of leaving the organization, who is likely to leave, and when to act, thus minimizing the costs and time associated with the recruitment process and improving performance. Furthermore, AI solutions help the development of individualized learning plans that help to define employees'professional goals and link them with the organization's strategy to encourage the employees'continuous growth. This paper explained how AI is impacting the retention process and how it can be used to decrease attrition rates, create a loyal workforce, and promote sustainable management of human and other resources. Furthermore, the author discusses the ethical issues, such as privacy and fairness of algorithms, that are involved in the implementation of AI systems. Thus, the above challenges can be solved by developing a sustainable and inclusive ecosystem that can help in the development of the future workforce. Based on a systematic review of literature, the study presents a framework that can help organizations improve their talent management practices with the help of AI to support long-term sustainable growth. It can be used to help industry professionals and decision-makers understand the new technological shifts that are occurring.
It is argued that successful digital HRM in Romania goes well beyond the simple adoption of new technologies, and depends on sound governance, effective human control, sustained investment in digital skills and genuine inclusion measures, all aligned with European standards.
Ionuț Drăgulescu, Daniel Danilov, Maria Dumitrache et al.· The Annals of the University...· 0 citations
The findings reveal that AI adoption in HRM is positively associated with both organizational performance and organizational efficiency, and HR process efficiency was found to play a mediating role in these relationships, indicating that improvements in HR processes are a key pathway through which AI generates organizational benefits.
O. Akintola, S. O. Chukwuedo, Imad Yasir Nawaz et al.· Journal of Business and Digi...· 0 citations
This research analyzes the utilization of artificial intelligence (AI) in human resource management (HRM) through a comprehensive assessment of existing literature to elucidate its applications, benefits, and obstacles. This paper explores the application of AI in HR operations using three research questions (RQ), evaluates the results reported in the literature along with the contributions of the past studies, and the main challenges faced in the implementation process. Outcomes reflect that AI can enhance effectiveness, decision-making, and coherence in recruiting workforce, performance management, and employee analytics. However, the studies also highlight serious challenges related to data accuracy, algorithmic bias, ethical and legal accountability, openness, and employee confidence. Using the information presented in previous researchers, this paper presents an organized review of the positive aspects of AI usage and issues of applying AI in HRM. The paper contributes to the increasing body of HR analytics literature by highlighting research gaps and synthesising previous works and also adds to the practical agenda by showcasing significant use of AIbased HRM in various functions and the related challenges faced in its implementation.
Ruksar Ali, Mohd Amanullah· Al-Barkaat Journal of Financ...· 0 citations
This paper examines how AI reshapes managerial decision-making by distinguishing decision augmentation from decision automation, and considers the governance tensions between centralized and decentralized approaches to AI deployment, as well as identifying the leadership competencies that gain value once routine managerial tasks are delegated to algorithmic systems.
R. Narenderajan· Scholedge International Jour...· 0 citations
This study investigates how organizational members concurrently perceive the benefits of artificial intelligence (AI) for knowledge management processes (KMPs) and the challenges involved in implementing AI within knowledge management systems (KMSs). Based on survey data from 378 respondents across diverse sectors and roles, the research employs validated instruments measuring perceptions of AI’s contribution to knowledge acquisition, documentation, sharing, and application, as well as perceived human, technological, financial, and ethical‑regulatory barriers. The results show a consistent positive relationship between perceived AI usefulness and perceived implementation barriers: individuals who attribute greater value to AI-enhanced knowledge processes also express heightened awareness of the complexities required to integrate AI into organizational systems. Knowledge documentation presents the strongest associations with all barrier categories, while knowledge sharing exhibits the weakest. Human‑related barriers emerge as the most pervasive across all processes, indicating the central role of employee readiness and organizational culture in shaping AI-enabled KM. These findings reveal a dual perception in which optimism regarding AI’s potential coexists with recognition of the organizational adjustments it demands. The study contributes to a more integrated understanding of AI adoption in KM, emphasizing that effective implementation requires aligning technological capabilities with human, cultural, and governance considerations.
M. Nakash, E. Bolisani· European Conference on Knowl...· 0 citations
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