Transformative AI in human resource management: enhancing workforce planning with topic modeling

Трансформационный потенциал ИИ в управлении человеческими ресурсами: совершенствование планирования трудовых ресурсов с помощью тематического моделирования
Raghu Raman, Murale Venugopal, Vandana Madhavan, Rajiv Prasad
2024-11-26

AI in human resource managementBERTopicalgorithmic biasethical AI governanceworkforce planning
This study explores the transformative role of artificial intelligence (AI) in human resource management (HRM), focusing on key functions such as recruitment, retention, and performance management. A comprehensive review was carried out PRISMA framework and BERTopic model on AI and HRM‑related keywords. The resulting publications were analyzed to extract meaningful topics. AI‑driven tools streamline candidate screening and interview analysis, significantly enhancing hiring efficiency and decision‑making accuracy. Concerns about algorithmic bias highlight the need for robust governance frameworks to ensure transparency and fairness in AI‑driven processes. The study emphasizes the importance of aligning AI adoption with Organizational Development principles to foster inclusivity and organizational justice. The integration of AI in performance management facilitates real‑time, objective performance assessments, although overreliance on such technologies can affect employee trust and engagement. Despite these advances, the study highlights ethical concerns surrounding data privacy and the potential for algorithmic bias. Addressing these challenges requires the implementation of comprehensive ethical frameworks to promote fairness and inclusivity in AI‑HRM applications. Strategically, AI transforms HR from a reactive function to a proactive, data‑driven partner aligned with long‑term organizational goals. Successful AI integration depends on governance mechanisms that uphold ethical standards, foster employee trust, and ensure transparency, enabling organizations to fully leverage AI’s potential in enhancing workforce management.
1
AI enables real-time, more objective performance assessments, but overreliance on these systems may reduce employee trust and engagement.
2
AI-driven recruitment tools streamline candidate screening and interview analysis, improving hiring efficiency and decision-making accuracy.
3
Algorithmic bias and data privacy are major ethical risks requiring governance frameworks that ensure transparency, fairness, and inclusivity.
4
Strategic AI adoption can shift HR from a reactive function toward a proactive, data-driven partner aligned with long-term organizational goals.
5
The study combines a PRISMA-based review with BERTopic modeling to identify key themes in AI applications for human resource management.

AI-driven human resource management processes, including recruitment, retention, performance management, and workforce planning

The transformative effects, benefits, risks, and governance requirements of AI adoption for workforce-management efficiency, decision-making accuracy, fairness, transparency, employee trust, and organizational inclusivity

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2024-11-26
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Authors
Raghu Raman
Murale Venugopal
Vandana Madhavan
Rajiv Prasad
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