Generative AI is potentially efficient in the newsrooms, but raises concerns about the issue of credibility and trust. We evaluate its effect and the results of 600 articles each with a stratified content analysis of each production mode (human/AI-assisted/AI-generated) and with disclosure (none/minimal/rich) (1) to determine its effect on accuracy, sourcing, and correction latency; (2) a preregistered 3 × 3 experiment manipulating production mode and disclosure (none/minimal/rich) to determine its effect on perceived article credibility and brand trust. Higher error and hallucination rates and fewer named sources, and slower corrections of AI-generated items are demonstrated by content analysis. Minimal AI labels diminish credibility and trust experimentally, but rich, process-level disclosure, naming, editorial verification, and sources mitigate penalties of work assisted by AI. We give policy and legitimacy implications to the newsroom.

This study explores public trust in Grok, an AI fact-checking tool on X (Twitter), during the 2025 Pakistan-India war. Using Media Dependency Theory, it examines how Grok shaped trust, fact-checking behavior, and perceptions of journalistic authority. A mixed-methods survey of 380 respondents measured trust, dependency, and views on AI’s role in crisis reporting. Findings show moderately high trust in Grok, moderate trust in journalists, and a perception that Grok was more reliable during the conflict. However, most participants favored human-AI collaboration over replacing reporters. Dependency on Grok was moderate and positively linked to trust. While respondents feared misinformation, they still valued AI for verification. Overall, the study suggests AI will not replace journalism but is becoming a parallel authority, influencing how audiences navigate uncertainty in conflict situations.