THE EVOLUTION OF ARTIFICIAL INTELLIGENCE IN JOURNALISM: A BIBLIOMETRIC ANALYSIS OF SCIENTIFIC PRODUCTION (1992-2025)

Abstract

The integration of Artificial Intelligence (AI) into journalism has evolved from experimental automation to a central disruptive force, fundamentally reshaping news production, distribution, and professional ethics. This study presents a comprehensive bibliometric analysis of the scientific literature at the intersection of AI and journalism to map its intellectual structure, evolutionary trends, and global collaboration networks. Analyzing 379 documents retrieved from the Web of Science Core Collection between 1992 and 2025, the study employs performance analysis and science mapping techniques using the Bibliometrix R-package. Results indicate an exponential surge in scientific production beginning in 2018, driven by the advent of generative AI and large language models. Thematic analysis reveals a shift from early focus on “robot journalism” and routine automation to complex inquiries regarding algorithmic transparency, deepfakes, and the “hybrid professional” role of journalists. Geographically, the field is dominated by research hubs in the United States, Spain, and the United Kingdom, highlighting a significant disparity in contributions from the Global South. The findings suggest that while AI journalism is maturing into a distinct subfield, urgent attention is required to address ethical governance and the pedagogical adaptation of journalism education to this algorithmic paradigm.

Keywords: Artificial intelligence, journalism, bibliometric analysis, automated journalism, generative AI, algorithmic ethics, newsroom automation.