Technology, trust, and industry transformation : a cross-national study on journalists' perceptions of field dynamics amid generative AI
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[EMBARGOED UNTIL 12/01/2026] Journalism has long been influenced by technologies, but generative AI introduces new possibilities and uncertainties for journalism by creating human-like content. Drawing on field theory, this study explores how journalists in the U.S. and China understand the socially embedded dynamics of the journalistic field amid the rise of generative AI, including its role in professional practices and its connections to power relations. Based on 29 in-depth interviews with journalists, 15 from the U.S. and 14 from China, the study finds that both countries are experiencing a transitional stage marked by hybrid and experimental habitus. Flexible newsroom guidance and a shared practical sense lead journalists to engage with generative AI in self-directed ways. Meanwhile, clear cross-national differences appear in AIgenerated visual workflows and in how journalists perceive and weigh forces inside and outside the journalistic field, which shape their understandings of what constitutes legitimate uses of generative AI. U.S. journalists emphasize social capital and prioritize audience trust, resulting in a more cautious approach to AI-generated visuals. In contrast, Chinese journalists emphasize on state-led media transformation policies and tend to internalize these national priorities, viewing experimentation with AI-generated visuals as a legitimate way to fulfill them. By moving beyond technocentric perspectives, this study offers a socially grounded analysis of how journalists interpret and engage with generative AI and advances comparative understanding of global journalism amid emerging technological change.
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M.A.