Author
Listed:
- Dalia Elsheikh
(Department of Communication and Journalism, Bournemouth University, UK)
- Daniel Jackson
(Department of Communication and Journalism, Bournemouth University, UK)
Abstract
Scholarship on AI and journalism in the Global South has highlighted how digital and data colonialism reproduce global hierarchies of power, labour, and knowledge, often through platform capitalism and externally controlled technological infrastructures. Yet limited empirical research examines how newsrooms in the Global South navigate these asymmetries in practice. This article analyses how Al-Masry Al-Youm, one of Egypt’s leading news organisations, integrates AI into editorial and technical operations under structural dependency. Drawing on in-depth interviews with journalists, editors, and technical staff, it examines how the newsroom adopts, adapts, and governs AI across data journalism, fact-checking, and generative applications. The findings show that reliance on global technology providers embeds forms of platform dependency within newsroom operations, while journalists and editors exercise bounded and situational agency through local adaptation, self-training, and the development of ethical guardrails that institutionalise responsible use. At the same time, AI adoption intensifies existing sustainability challenges, as journalistic content and labour increasingly support AI systems without corresponding financial return. To make sense of these findings, we introduce the concept of “defensive AI governance,” showing how AI adoption is managed through organisational practices of limitation, supervision, and infrastructural self-protection. By grounding this concept in organisation‑level evidence from the Global South, the study contributes to debates on platform power, journalistic agency, and AI governance in journalism.
Suggested Citation
Dalia Elsheikh & Daniel Jackson, 2026.
"Platformisation, Power, and AI Governance in the Newsroom: Insights From the Global South,"
Media and Communication, Cogitatio Press, vol. 14.
Handle:
RePEc:cog:meanco:v14:y:2026:a:12361
DOI: 10.17645/mac.12361
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