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    Utilization of artificial intelligence in HR: upskilling employees in real-time manner

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    ICEBTM-25-1215.pdf (291.2Kb)
    Date
    2025-11
    Author
    Chakrabortty, Krishanu
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    Abstract
    Artificial Intelligence (AI) is transforming global human resource (HR) practices, but its adoption in emerging economies such as Bangladesh remains at an early stage. As AI continues to evolve, ongoing research into its organizational impact is essential. This study examines AI-driven Human Resource Information Systems (HRIS) and their impact on employee training and organizational learning in Bangladesh. The study adopts a qualitative research approach based on interviews with HR professionals and employees involved in daily HR operations. It analyzes the current integration of HRIS, challenges associated with AI implementation, including cost, technical expertise, and privacy concerns, and the readiness of the workforce. The findings reveal strong optimism regarding the potential return on investment despite relatively low adoption rates, with infrastructure gaps and the need for cultural adaptation acting as significant moderating factors. The research supports the applicability of the Technology Acceptance Model (TAM) and Diffusion of Innovation (DOI) theories in this context and proposes strategies for effective AI-HRIS implementation. By addressing workforce familiarity gaps, cost constraints, infrastructure limitations, and privacy concerns, organizations in Bangladesh can leverage AI to develop more efficient and personalized HR processes.
    URI
    https://icebtm.iub.edu.bd
    https://ar.iub.edu.bd/handle/11348/1496
    Collections
    • International Conference on Economics, Business and Technology Management (ICEBTM 2025) [124]
    Publisher:
    School of Business and Entrepreneurship, Independent University, Bangladesh (IUB)
    Type:
    Conference paper
    Keywords:
    Adaptive training & development, AI based learning, Artificial Intelligence (AI), Employee upskilling, Organizational learning, Performance management, Technology adoption
    DOI:
    https://doi.org/10.67508/iub.icebtm.2025.090

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