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National Conditions for AI Innovation in Journalism: How innovation capacity, media systems, and professional roles predict AI award recognition across 25 countries

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  • Juliane A. Lischka

Abstract

AI awards serve as a mechanism for legitimizing technological innovation. Recognition through such awards positions recipients as influential actors in shaping how AI is applied within journalism. But why do some countries lead in journalistic AI award recognition while others lag behind? Drawing on Innovation Systems Theory, this study explores how national innovation capacity, media system structures, and journalistic role orientations influence international recognition for AI-driven journalism innovation. Using a cross-national comparative design, the analysis links secondary data on national indicators of innovation capacity, media system characteristics, and journalistic professionalism to international AI award recognition in the 2024 and 2025 Global Media Awards, organized by the International News Media Association (INMA). Results show that countries with strong national innovation capacity and watchdog-oriented journalistic cultures are more likely to receive recognition for AI innovation, while traditional media system characteristics and general professionalism show limited predictive power. The results highlight the importance of systemic conditions, rather than just organizational factors, in shaping how AI innovation is adopted in journalism. The study contributes to scholarship on media innovation and the global diffusion of AI in journalism.

Suggested Citation

  • Juliane A. Lischka, 2026. "National Conditions for AI Innovation in Journalism: How innovation capacity, media systems, and professional roles predict AI award recognition across 25 countries," Journal of Media Economics, Taylor & Francis Journals, vol. 38(2), pages 23-38, April.
    • Handle: RePEc:taf:jmedec:v:38:y:2026:i:2:p:23-38
    DOI: 10.1080/08997764.2025.2566700
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