A bibliometric analysis of the economic effects of using artificial intelligence and ChatGPT tools in higher education institutions

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One of the main challenges in higher education management is the complexity of resource optimization and increasing volumes of data, which limits the efficiency and accuracy of decision-making. The application of artificial intelligence can address these issues.
The present study aims to identify the key trends, knowledge gaps, and opportunities for further research into the economic effects of using artificial intelligence and ChatGPT tools in higher education. For this purpose, a systematic literature review was conducted to identify and screen the scientific articles related to the topic of this study indexed in Web of Science and Scopus from 1986 to 2024. A total of 234 articles were selected, all demonstrating positive growth both in scholarly output and citation count. The study identified the key contributors to scientific research on this topic by region (the United States, China, and India). It concluded that the relevant research centers are still at an early stage of their development. Based on bibliometric clusters formed by co-occurrence relations, three main areas of research were defined: 1) artificial intelligence in education for decision-making; 2) process automation and digital transformation in educational institutions; 3) artificial intelligence technologies and their application in education.
The study highlights the main areas of economic effects of artificial intelligence and ChatGPT tools in higher education, including reducing administrative costs, saving time for teachers and students, and improving the quality and accessibility of educational process.

Acknowledgments
The publication is part of the research topic “Economic Basics of Technology Diffusion into the National Economy of Ukraine Considering Best International Practices” (№0124U003482).

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    • Figure 1. PRISMA flow diagram
    • Figure 2. Document and citation dynamics of selected publications
    • Figure 3. Quantitative characteristics of the main keywords
    • Figure 4. Bibliometric clusters of the main keywords
    • Figure 5. Time-scale distribution of the main keywords
    • Table 1. Main keywords
    • Table 2. Top five key contributors to scientific research by region, institution, and the number of publications in scientific journals from 2014 to 2024
    • Table 3. Bibliometric cluster profiles defining research areas in economic effects of using AI and ChatGPT in higher education
    • Table 4. Systematization of potential economic effects of using AI and ChatGPT in higher education
    • Conceptualization
      Anna Vorontsova, Svitlana Tarasenko, Artem Bilovol
    • Formal Analysis
      Anna Vorontsova, Svitlana Tarasenko
    • Methodology
      Anna Vorontsova, John Soss
    • Software
      Anna Vorontsova, Wojciech Duranowski
    • Visualization
      Anna Vorontsova
    • Writing – original draft
      Anna Vorontsova, Svitlana Tarasenko, Wojciech Duranowski, Arkadiusz Durasiewicz, John Soss, Artem Bilovol
    • Writing – review & editing
      Anna Vorontsova, Svitlana Tarasenko
    • Funding acquisition
      Svitlana Tarasenko
    • Investigation
      Svitlana Tarasenko, Arkadiusz Durasiewicz, John Soss, Artem Bilovol
    • Supervision
      Svitlana Tarasenko, Wojciech Duranowski, John Soss
    • Data curation
      Wojciech Duranowski, Arkadiusz Durasiewicz, Artem Bilovol
    • Resources
      Wojciech Duranowski, Arkadiusz Durasiewicz, Artem Bilovol
    • Validation
      Arkadiusz Durasiewicz
    • Project administration
      John Soss, Artem Bilovol