THE EVOLUTION OF ARTIFICIAL INTELLIGENCE LITERACY RESEARCH: A BIBLIOMETRIC ANALYSIS
DOI:
https://doi.org/10.35631/JISTM.1144026Keywords:
AI Literacy, Artificial Intelligence, AI Technology, Bibliometric Analysis, Generative AIAbstract
The rapid adoption of artificial intelligence and growing concerns regarding workplace disruption and misinformation, traditional digital literacy frameworks lack updated, systematic mapping to account for the disruptions brought by generative AI. To address this gap, this study identify annual research trends, identifies dominant topics, and evaluates the intellectual structure of AI literacy literature published between 2020 and 2025. Literature was retrieved from the Scopus database following PRISMA systematic screening guidelines and analyzed using VOSviewer for science mapping, Harzing’s Publish or Perish for citation metrics, and Microsoft Excel. A final dataset of 443 records was selected for bibliometric analysis. The analysis reveals an exponential growth in scholarly output, peaking in 2025 with 292 documents (65.91%). The United States (85 publications) and China (80 publications) are the leading research contributors, S.C. Kong is identified as the most prolific author (17 publications), and Computers and Education: Artificial Intelligence serves as the top publication source (25 publications). Analysis also demonstrates a central focus on educational technology and digital competency, with rapidly emerging themes including prompt engineering, academic integrity, large language models, AI ethics and teacher education. This study contributes to the literature by providing a longitudinal evaluation of the post-ChatGPT AI literacy landscape, offering an empirical foundation to inform future policy development and responsible AI integration frameworks.
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References
Cao, Y., & Zhai, J. (2023). Bridging the gap–the impact of ChatGPT on financial research. Journal of Chinese Economic and Business Studies, 1-15.
Chiu, T. K. F., Ahmand, Z., Ismail, M., & Sanusi, I. T. (2024). What are artificial Intelligence literacy and competency? A comprehensive framework to support them. Computers & Education Open, 6, 100171. https://doi.org/10.1016/j.caeo.2024.100171
Donthu, N., Kumar, S., Mukherjee, D., Pandey, N. & Lim, W.M. (2021). How to conduct a bibliometric analysis: an overview and guidelines. Journal of Business Research, 133, 285-296. doi: https://doi.org/10.1016/j.jbusres.2021.04.070.
Dwivedi, Y. K., Kshetri, N., Hughes, L., Slade, E. L., Jeyaraj, A., Kar, A. K., . . . Ahuja, M. (2023). “So what if ChatGPT wrote it?” Multidisciplinary perspectives on opportunities, challenges and implications of generative conversational AI for research, practice and policy. International Journal of Information Management, 71, 102642.
Jan Jöhnk, Malte Weißert & Katrin Wyrtki. (2021). Ready or Not, AI Comes— An Interview Study of Organizational AI Readiness Factors. Bus Inf Syst Eng 63, 5–20. https://doi.org/10.1007/s12599-020-00676-7
Jarrahi, M. H., Askay, D., Eshraghi, A., & Smith, P. (2023). Artificial intelligence and knowledge management: A partnership between human and AI. Business Horizons, 66(1), 87-99.
Jonathan, G.& Bin, L. (2018). The Application of Medical Artificial Intelligence Technology in Rural Areas of Developing Countries. Narrative Review, 2 (1), 174-181. DOI: 10.1089/heq.2018.0037.
Laupichler, M. C., Aster, A., Haverkamp, N., & Raupach, T. (2023). Development of the “scale for the assessment of non-experts’ AI literacy” – An exploratory factor analysis. Computers in Human Behavior Reports, 12. https://doi.org/10.1016/j. chbr.2023.100338
Long, D., & Magerko, B. (2020). What is AI literacy? Competencies and design considerations. Proceedings of the 2020 CHI conference on human factors in computing systems (2020), pp. 1-16, 10.1145/3313831.3376727
Lund B. D., et al. (2023). ChatGPT and a new academic reality: Artificial Intelligence-written research papers and the ethics of the large language models in scholarly publishing. Journal of the Association for Information Science and Technology 74(5): 570–581.
Mills, K., Ruiz, P., Lee, K., Coenraad, M., Fusco, J., Roschelle, J. & Weisgrau, J. (2024, May). AI Literacy: A Framework to Understand, Evaluate, and Use Emerging Technology. https://doi.org/10.51388/20.500.12265/218
Misra, V. P., Mishra, P. K., & Sharma, A. (2023). Artificial intelligence in Education – Emerging Trends, Thematic Analysis and Application in Lifelong Learning. IEEE Asia-Pacific Conference on Computer Science and Data Engineering (CSDE), 2023, pp. 1–6. doi: 10.1109/CSDE59766.2023.10487664.
Moher, D., Liberati, A., Tetzlaff, J. and Altman, D.G. (2009). Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. PLoS Medicine,6(7), e1000097, doi: https://doi.org/10.1371/journal.pmed.1000097.
Nasrallah R (2014). Learning outcomes’ role in higher education teaching. Education, Business and Society: Contemporary Middle Eastern Issues, 7(4); 257–276, doi: https://doi.org/10.1108/EBS-03-2014-0016
Prashant L., Xiaoting, H., Linxiu, Z., Jianguo, W., Hongmei, Y., Yingquan, S., Yaojiang, S., & James C. (2016). The Impact of Vocational Schooling on Human Capital Development in Developing Countries: Evidence from China. The World Bank Economic Review, 30(1), 143-170. https://doi.org/10.1093/wber/lhv050.
Trigka, Maria & Dritsas, Elias. (2025). The Evolution of Generative AI: Trends and Applications. IEEE Access. 13. 98504 - 98529. 10.1109/ACCESS.2025.3574660.
Valtonen, T., Tedre, M., Makitalo, K., & Vartiainen, H. (2019). Media literacy educationin the age of machine learning. Journal of Media Literacy Education, 11(2), 20–36. https://doi.org/10.23860/jmle-2019-11-2-2
