Digital news organizations increasingly adopt generative artificial intelligence (GenAI) under conditions of economic strain and platform dependency. While AI integration is often framed as a strategy for operational efficiency, its institutional implications extend beyond productivity gains. This study examines how different governance approaches to GenAI adoption—specifically variations in transparency, disclosure, and oversight practices—correspond to shifts in audience engagement and financial performance. Using a comparative mixed-methods design, we analyze three prominent cases between 2022 and 2025—CNET, Gizmodo, and The New York Times—representing, respectively, covert AI use with limited disclosure, transparent but poorly managed deployment, and proactive ethical and legally grounded positioning. To operationalize audience stability, we introduce two behavioral indicators: the Engagement Resilience Index (ERI), measuring depth and consistency of user engagement; and the Market Turbulence Ratio (MTR), capturing post-incident volatility in audience behavior. The findings indicate that AI deployment strategies associated with limited disclosure or weak governance correspond with increased engagement instability and revenue contraction, whereas approaches framed through institutional accountability and ethical positioning align with more stable or positive performance trajectories. The results suggest that AI integration functions not merely as a technological shift but as a governance-mediated signal interpreted by audiences in economic terms. These dynamics highlight the centrality of institutional trust in shaping the sustainability of digital journalism in the age of automation.
Iavich et al. (Thu,) studied this question.