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Unravelling the Impact of Generative Artificial Intelligence (GAI) in Industrial Applications: A Review of Scientific and Grey Literature

Author

Listed:
  • Arpan Kumar Kar

    (Indian Institute of Technology Delhi)

  • P. S. Varsha

    (Presidency University)

  • Shivakami Rajan

    (Ramaiah University of Applied Science)

Abstract

The scope of application of generative artificial intelligence (GAI) in industrial functions is gaining high prominence in academic and industrial discourses. In this article, we explore the usage of GAI and large language models (LLMs) in industrial applications. It promises myriad advantages such as greater engagement, cooperation and accessibility. LLMs like ChatGPT are able to evaluate unstructured queries, assess alternatives and offer actionable advice to users. It is being used to produce fast reports, flexible responses, environment scanning capabilities and insights that can enhance organisation flexibility in making better and quicker decisions, improving customer experiences and thereby augmenting firm profitability. This article offers a comprehensive review of scientific and grey literature in GAI and language models. The synthesis of complementary sources of information brings exciting perspectives in this fast evolving field. We provide directions surrounding future use of GAI as well as research directions for management researchers.

Suggested Citation

  • Arpan Kumar Kar & P. S. Varsha & Shivakami Rajan, 2023. "Unravelling the Impact of Generative Artificial Intelligence (GAI) in Industrial Applications: A Review of Scientific and Grey Literature," Global Journal of Flexible Systems Management, Springer;Global Institute of Flexible Systems Management, vol. 24(4), pages 659-689, December.
    • Handle: RePEc:spr:gjofsm:v:24:y:2023:i:4:d:10.1007_s40171-023-00356-x
    DOI: 10.1007/s40171-023-00356-x
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