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Success factors and development areas for the implementation of Generative AI in companies

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  • Meyer, Julian Anton

Abstract

With the significant increase in public interest in ChatGPT since its breakthrough following the public release in November 2022, an expanding array of application possibilities is being discovered. This heightened interest is also reflected in economic contexts and for businesses. These Generative AI (GenAI) models are believed to have the potential to contribute trillions of dollars in value to the global economy. Now, pioneering companies face the challenge of successfully leveraging this Generative AI technology to their advantage, positioning themselves successfully at the forefront of AI. The adoption of Generative AI proves to be neither straightforward nor simple for companies and is associated with various challenges. Within this thesis, these challenges will be identified by conducting a multiple-case study involving expert interviews. Practical insights will be obtained to identify the decisive factors for the successful adoption of Generative AI, and these insights will be translated into a hands-on implementation framework for companies.

Suggested Citation

  • Meyer, Julian Anton, 2025. "Success factors and development areas for the implementation of Generative AI in companies," Junior Management Science (JUMS), Junior Management Science e. V., vol. 10(1), pages 1-23.
    • Handle: RePEc:zbw:jumsac:313858
    DOI: 10.5282/jums/v10i1pp1-23
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    References listed on IDEAS

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    1. Shijie Wu & Ozan Irsoy & Steven Lu & Vadim Dabravolski & Mark Dredze & Sebastian Gehrmann & Prabhanjan Kambadur & David Rosenberg & Gideon Mann, 2023. "BloombergGPT: A Large Language Model for Finance," Papers 2303.17564, arXiv.org, revised Dec 2023.
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