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Unlocking training transfer in the age of artificial intelligence

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  • Park, Jennifer Jihae

Abstract

In today's rapidly evolving world, the need for effective training and development programs is more urgent than ever. The biggest challenge to training research stems from the advancement of technology such as artificial intelligence. This article is organized into three sections. First, I present an overview of integrating emerging technology—artificial intelligence—in the workplace. Second, I discuss strategies to keep up with rapidly changing work environments for effective and timely training transfer. Third, I conclude with future directions for training transfer in the era of artificial intelligence. This study does not focus on “what we know” in training transfer research. Rather, it emphasizes future directions and offers recommendations for improving training and training transfer through the advancement of technology and by facilitating dynamic work environments. The recommendations aim to develop more effective training programs that will lead to significant and sustainable improvements in employee performance, productivity, and organizational outcomes.

Suggested Citation

  • Park, Jennifer Jihae, 2024. "Unlocking training transfer in the age of artificial intelligence," Business Horizons, Elsevier, vol. 67(3), pages 263-269.
    • Handle: RePEc:eee:bushor:v:67:y:2024:i:3:p:263-269
    DOI: 10.1016/j.bushor.2024.02.002
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    References listed on IDEAS

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    1. Jarrahi, Mohammad Hossein & Askay, David & Eshraghi, Ali & Smith, Preston, 2023. "Artificial intelligence and knowledge management: A partnership between human and AI," Business Horizons, Elsevier, vol. 66(1), pages 87-99.
    2. Alexander Maedche & Christine Legner & Alexander Benlian & Benedikt Berger & Henner Gimpel & Thomas Hess & Oliver Hinz & Stefan Morana & Matthias Söllner, 2019. "AI-Based Digital Assistants," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 61(4), pages 535-544, August.
    3. JunXia Zhang & Ying Yuan & Baiyuan Ding, 2022. "Multi-Dimensional Post Competency Evaluation Model in Human Resource Management under the Background of Artificial Intelligence," Mathematical Problems in Engineering, Hindawi, vol. 2022, pages 1-10, September.
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