Summary
This peer-reviewed study argues that AI is reshaping journalism less through sudden replacement than through the redistribution of concrete newsroom tasks and professional territory. Using 50 interviews in Nigerian newsrooms, the authors show journalists accepting AI for bounded production work such as transcription, copyediting, and preliminary drafting while trying to hold onto final editorial judgment and higher-status reporting functions.
Why It Matters
This is a strong direct journalism story because it maps AI use at the level of job boundaries and workflow redistribution.
- it documents concrete newsroom use of AI for transcription, copyediting, and early drafting rather than generic enthusiasm
- it shows three distinct responses to AI pressure: jurisdictional maintenance, hybrid labor, and jurisdictional retreat
- it matters because it treats AI adoption as a labor and professional-boundary problem, not just a product or policy issue
- it adds needed Global South reporting and research detail to a corpus that can otherwise skew toward US and UK examples
What the Source Says
The article reports on in-depth interviews with 50 journalists in Nigerian newsrooms and uses Abbott's sociology of professions to describe three response patterns: maintenance of core professional territory, hybrid labor configurations, and retreat from lower-status tasks. The abstract says journalists were primarily using AI for transcription, copyediting, and preliminary drafting, which the authors frame as tasks previously embedded inside normal editorial work and training. The paper argues that newsroom AI adoption is therefore not only about efficiency, but about who keeps control over core professional judgment and which parts of the work become more machine-mediated.