Purpose – In a period of rapid information dissemination, the spread of misinformation poses an important threat to public understanding and democratic processes. This study aims to examine the development of generative artificial intelligence (AI) models with the objective of automating the fact-checking of reports and reducing the impact of misinformation.

Design/methodology/approach – The study employed Bibliometrix R and VOS viewer tools to perform a thorough assessment of collaborative networks, research trends and important themes in the field of AI factchecking journalism. The data was retrieved from the Scopus database that includes 282 publications between 2022 and 2024 to provide a bibliometric study on influence of AI on fact-checking in journalism.

Findings – The results show a notable increase in scholarly research output and examined the top prominent authors, active organizations and nations/countries that are advancing AI fact-checking in journalism research. The study identifies commonly explored key themes, such as automation, disinformation and ethical problems and co-authorship networks.

Originality/value – This study seeks to fill knowledge gaps by mapping the conceptual structure of AI tools in journalism articles, thereby offering an in-depth understanding of AI’s evolving influence in journalism ethics and fact-checking.