Between Anticipation and Impact: Assessing Generative AI’s Influence on Journalistic Labor and Employment

This article explores the impact of generative artificial intelligence (genAI) on employment in journalism, drawing on 21 semi-structured expert interviews conducted in Flanders, Belgium. By examining how genAI technologies are strategically implemented, this research analyzes their consequent effects on labor dynamics and employment prospects within the profession. Contributing to the rapidly expanding scholarship on genAI and journalism, this article offers empirical insights into the evolving labor dynamics confronting media professionals. The findings reveal that genAI implementation mainly supports content distribution and routine tasks like transcribing and summarizing. Fully automated processes are implemented in news on sports and real estate transactions. These developments show that AI is currently not replacing news workers but is instead reconfiguring the profession by evolving the competencies and skillsets required of journalists. This happens through a combination of re-skilling, the upvaluing of new or existing skills (AI literacy, creative and digital storytelling, critical-analytical skills) and de-skilling, the devaluation of others (copy-editing, short news updates, traditional layouting). The article concludes by demonstrating how the narratives on labor and automation have barely changed over ten years despite significant technological advancements, and urges for more empirical research to prevent under- or overestimation of technology’s impact on journalism.