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© 2026 IJSREM – International Journal of Scientific Research in Engineering and Management. This is an open-access journal. Articles are published under the Creative Commons Attribution (CC BY 4.0) License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Paper ID:IJSREM64767

Strategic Integration of Artificial Intelligence in Virtual Human Resource Management and Talent Management: A Conceptual Framework for Modern Organizations

Stream/Area:

-

Subject:

-

Paper ID:

IJSREM64767

Volume:

10 |

6 |

Jun 2026

Pages:

1-4

Publication Frequency:

Monthly (12 issues per year)

DOI
Digital Object Identifier
10.55041/IJSREM64767

License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.

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Authors

Akshaya Meenakshi. S

Akshaya Meenakshi. S

Department of Management Studies

Periyar University

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DPT

Dr. P. Thirumoorthi

Department of Management Studies

Periyar University

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Anandha Bapu. A

Anandha Bapu. A

Department of Management Studies

Periyar University

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Abstract

The rapid digitalization of the workplace has fundamentally reshaped human resource management, with artificial intelligence emerging as a transformative force across HR functions. This conceptual article examines the strategic integration of AI within virtual human resource management (VHRM) and talent management (TM) systems. Drawing on a synthesis of recent literature published between 2020 and 2026, the article analyzes how AI technologies are redefining talent acquisition, performance evaluation, workforce planning, and employee development in increasingly virtualized work environments. The findings reveal that while AI adoption in HR has reached 61% of organizations, mature integration remains limited, with talent acquisition dominating implementation at 77% and strategic workforce planning lagging at just 11%. The article proposes a strategic framework that integrates AI capabilities across the talent lifecycle within virtual HR architectures, addressing both opportunities and critical challenges including algorithmic bias, data privacy, transparency deficits, and the imperative for hybrid human–AI decision models. Practical recommendations are offered for HR professionals seeking to harness AI’s potential while maintaining ethical governance and human-centric values in an agentic future.

KEYWORDS

Artificial Intelligence Virtual Human Resource Management Talent Management Strategic Workforce Planning Algorithmic HRM

Cite This Article

Akshaya Meenakshi. S, Dr. P. Thirumoorthi, Anandha Bapu. A, "Strategic Integration of Artificial Intelligence in Virtual Human Resource Management and Talent Management: A Conceptual Framework for Modern Organizations," International Journal of Scientific Research in Engineering and Management, vol. 10, no. 6, pp. 1-4, Jun 2026. https://doi.org/10.55041/IJSREM64767

Full Article/Conclusion

Artificial intelligence is fundamentally reshaping virtual human resource management and talent management, offering unprecedented capabilities for data-driven decision-making, process automation, and personalized employee experiences. However, the current state of AI adoption—dominated by talent acquisition applications while lagging in strategic workforce planning—reflects a pattern of incremental optimization rather than transformational integration. The organizations that will thrive in the coming decade are those that move beyond viewing AI as a tool for efficiency and embrace it as an architectural element for reimagining how talent is attracted, developed, deployed, and retained in virtualized work environments.   The path forward requires balancing technological advancement with ethical governance, automation with human judgment, and efficiency with fairness. As agentic AI systems become increasingly capable, HR’s role will evolve from process administrator to strategic integrator—designing hybrid talent systems where humans and AI collaborate to achieve organizational outcomes while safeguarding the human values that make work meaningful. The question is not whether AI will transform HR, but whether organizations will lead this transformation with wisdom, responsibility, and vision.

References

1.      Afshari, Leila, Muhammad Shakil Ahmad, and Talha Mansoor. 2023. “How to Lead Responsibly toward Enhanced Knowledge Sharing Behavior and Performance: Implications for Human Resource Management.” PERSONNEL REVIEW. 2.      Al-Alawi, A. I., and F. A. Albinali. 2024. “Unveiling the Retention Puzzle for Optimizing Employee Engagement and Loyalty Through Analytics-Driven Performance Management: A Systematic Literature Review.” Pp. 292–96 in. 3.      Almheiri, H. M., S. Z. Ahmad, A. R. Abu Bakar, and K. Khalid. 2024. “Artificial Intelligence Capabilities, Dynamic Capabilities and Organizational Creativity: Contributing Factors to the United Arab Emirates Government’s Organizational Performance.” Journal of Modelling in Management 19(3):953–79. doi:10.1108/JM2-11-2022-0272. 4.      Al-Omari, M., M. Rahrouh, and Y. Karsoo. 2023. “Human Resource Management and AI: Does It Really Help?” 5.      Bankins, Sarah. 2021. “The Ethical Use of Artificial Intelligence in Human Resource Management: A Decision-Making Framework.” ETHICS AND INFORMATION TECHNOLOGY 23(4):841–54. 6.      Dawson, J. Y., and E. Agbozo. 2024. “AI in Talent Management in the Digital Era – an Overview.” Journal of Science and Technology Policy Management. doi:10.1108/JSTPM-06-2023-0104. 7.      Kadirov, A., Y. Shakirova, G. Ismoilova, and N. Makhmudova. 2024. “AI in Human Resource Management: Reimagining Talent Acquisition, Development, and Retention.” in Int. Conf. Knowl. Eng. Commun. Syst., ICKECS. Institute of Electrical and Electronics Engineers Inc. 8.      Khan, Imran Ahmed, and Carolyn John. 2025. “Unveiling the Workforce Renaissance: How Hybrid Work Models, Employee Engagement, and Technology 4.0 Shape Employee Performance.” Management 13(4):186–201. 9.      Kumar, Sourabh. 2022. “The Impact of Talent Management Practices on Employee Turnover and Retention Intentions.” Global Business and Organizational Excellence 41(2):21–34. doi:10.1002/joe.22130. 10.   Liu, Li, and Seechen Yong. 2022. “Optimization of Digital Management Path for Human Resource Performance Evaluation Based on Multiobjective Decision-Making Mathematical Model.” MOBILE INFORMATION SYSTEMS 2022.

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Publication Date

6/10/2026

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Review Rounds: 2

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Conflict of Interest

The authors declare no conflict of interest related to this research work.

Funding Information

Funding Agency: Indian Council of Social Science Research (ICSSR Full-Term Doctoral Fellowship)

Grant / Project ID: ICSSR/RFD/2025-26/OBC/246

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