The Impact of Generative Artificial Intelligence on Human Resource Decision-Making, Talent Acquisition, and Workforce Planning in Knowledge-Based Organizations

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@article{1707186,
      author = {Dr. Hegde Lata Narayan},
      title = {The Impact of Generative Artificial Intelligence on Human Resource Decision-Making, Talent Acquisition, and Workforce Planning in Knowledge-Based Organizations},
      journal = {Iconic Research And Engineering Journals},
      year = {2025},
      volume = {8},
      number = {8},
      pages = {1035-1045},
      issn = {2456-8880},
      url = {https://www.irejournals.com/formatedpaper/1707186.pdf},
      abstract = {This conceptual study synthesizes insights from strategic human resource management, organizational theory, and emergent AI governance literature to examine the design and governance of generative AI (GAI) systems such adaptive content-generating, reasoning-simulating AI systems capable of multi-turn, contextual interaction in reshaping the?core HR function of human resource decision making, talent acquisition, and workforce planning in knowledge-based organizations beyond merely automation and predictive analytics; adopting an integrative conceptual approach based on an extensive synthesis of peer-reviewed HRM research, digital transformation studies, and ethical AI frameworks. This paper argues that generative AI reconstitutes HR work by redistributing decision power among human actors and algorithmic outputs, reshuffling responsibility for HR outcomes in candidate evaluation, skills assessment, workforce development, and?talent planning; the paper specifically argues that generative AI improves the speed, consistency, and scenario modeling capacity of decisions in knowledge-intensive contexts while inadvertently increasing risks connected with opacity, bias amplification, over-reliance on algorithmic returns, and loss of professional judgment; resulting in a transformation of HR decision-making from an entirely human-driven process to a hybrid human?AI collaboration; on the basis of these arguments, the study introduces an extensive conceptual framework that connects generative AI capabilities with HR results through intermediary drivers such as decision augmentation, data-driven sense making, and dynamic skills intelligence; alongside the moderating role of AI literacy, responsible governance, and organizational culture; in addition, a theory-based set of research propositions is developed to shape future empirical studies on the contextual factors that influence the performance of generative AI in relation to talent acquisition efficiency, workforce planning, and strategic HR value creation; the paper advances our understanding of the HRM and digital management literatures by extending existing strategic HR decision-making models, re-conceptualizing HR professionals as 'sensemakers' when it comes to generative AI rather than passive system users, and establishing a structured foundation for conceptualizing generative AI as a strategic but ethically burdensome organizational resource; ultimately, this study provides significant managerial implications as it highlights the necessity for responsible adoption of generative AI, sound governance mechanisms, continuous upskilling of HR professionals, and transparency of accountability mechanisms so that HR practices based on generative AI can contribute to long term sustainable, equitable, and people-centric HR in knowledge-based organizations.},
      keywords = {Generative Artificial Intelligence, Strategic Human Resource Management, Human?AI Collaboration, Talent Acquisition, Workforce Planning, HR Decision-Making},
      month = {February},
      doi = {https://doi.org/10.64388/IREV8I8-1707186}
  }