The structural transformation of the news ecosystem driven by generative artificial intelligence has redefined fundamental concepts such as media authority, gatekeeping, and public trust. This research primarily aims to identify and explain the applications of artificial intelligence within the news ecosystem of the IRIB News Agency. Methodologically, this study is applied in purpose, qualitative in data type, and exploratory in nature. Data were collected through library research and semi-structured in-depth interviews with 15 experts and specialists in the fields of AI, news, and media. Data analysis was conducted using the thematic analysis method.The findings indicate that AI applications are categorized into seven key dimensions: "Intelligent Information Retrieval and Monitoring," "Content Production and Editing," "Information Dissemination and Impact Assessment," "Archive and Big Data Management," "Validation and Ethical Governance," "Policy-making and Infrastructure," and "Organizational Consequences and Human-Machine Interaction" . The results suggest that by shifting the paradigm from manual search to automated reception and automating repetitive tasks, AI elevates the journalist's role from a "production technician" to a "content strategist" (or content architect).Ultimately, the study emphasizes the necessity of implementing the "Human-in-the-Loop" (HITL) model to leverage machine speed while ensuring that final judgment and ethical responsibility remain anchored in human intellect. Furthermore, the localization of Large Language Models (LLMs) and the development of domestic infrastructure are proposed as strategic imperatives to safeguard data sovereignty and mitigate algorithmic biases.