Article | Open Access
AI Adoption in Indonesian and Malaysian Journalism: A Comparative Mixed-Methods Study
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Abstract: Artificial intelligence (AI) is reshaping journalistic practice worldwide, automating tasks such as transcription, translation, content generation, data analysis, and personalisation. News organisations across the Global South are also experimenting with public-facing applications of AI, including AI-generated anchors and reporters. These developments challenge assumptions about technological lag in non-Western newsrooms, revealing how competitive pressures, resource constraints, and platform dependency can drive distinctive modes of technological adoption. This article compares Indonesian and Malaysian journalists’ attitudes toward AI and their intentions to integrate these technologies into their professional practice. Using a convergent parallel mixed-methods approach grounded in the technology acceptance model, the study analyses how perceived usefulness, ease of use, and social norms influence decisions about the adoption of AI in news production. While both countries demonstrate strong links between usability and perceived value, cross-national differences in how these measures influence adoption intentions highlight how local contexts inflect journalists’ attitudes. Interviews further reveal that acceptance is shaped not only by individual attitudes but by policy, market dynamics, infrastructure, generational dynamics, and anxieties about technological displacement. This article advances the study of individual journalists’ attitudes toward AI within a critical, contextually grounded approach to technological adoption.
Keywords: artificial intelligence; Global South; Indonesia; journalism; Malaysia; technology acceptance
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Vol 14 (2026): AI Use in Marginalized Media Markets (In Progress)
© Indra Prawira, Mastura Mahamed, Tai Neilson. This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 license (http://creativecommons.org/licenses/by/4.0), which permits any use, distribution, and reproduction of the work without further permission provided the original author(s) and source are credited.


