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Text-Based Insights on Generative AI Applications in Economics and Business

Author

Listed:
  • Morteza Alaeddini

    (ICN Business School, CEREFIGE - Centre Européen de Recherche en Economie Financière et Gestion des Entreprises - UL - Université de Lorraine)

  • Asgari Alireza

    (UGA INP IAE - Grenoble Institut d'Administration des Entreprises - UGA - Université Grenoble Alpes - Grenoble INP - Institut polytechnique de Grenoble - Grenoble Institute of Technology - UGA - Université Grenoble Alpes, CERAG - Centre d'études et de recherches appliquées à la gestion - UGA - Université Grenoble Alpes)

  • Shahab Ahmadi

    (UGA - Université Grenoble Alpes)

Abstract

This study provides a thorough bibliometric text-based analysis of generative artificial intelligence (GenAI) research in economics and business. Based on an analysis of 1,613 peer-reviewed articles from Scopus and Web of Science published between 2021 and 2025, the study uses co-occurrence networks, topic modelling and burst analysis to map the intellectual structure of GenAI literature. The key findings reveal GenAI to be a rapidly evolving and increasingly interdisciplinary field, with research hotspots in AI ethics, sentiment analysis, digital transformation, and higher education. Emerging trends include AI-assisted writing, consumer behaviour and strategic management applications. The study highlights the growing integration of GenAI in business functions and educational contexts, while also identifying ethical and methodological challenges. This work offers valuable insights for scholars, educators and practitioners seeking to understand the dynamic landscape and future directions of GenAI in business and economics.

Suggested Citation

  • Morteza Alaeddini & Asgari Alireza & Shahab Ahmadi, 2025. "Text-Based Insights on Generative AI Applications in Economics and Business," Post-Print hal-05356064, HAL.
    • Handle: RePEc:hal:journl:hal-05356064
    DOI: 10.1504/IJGAIB.2025.10073998
    as

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