Future of Work and Digital Management Journal 3 Serial Number 8 2025 06 29 Media Content Policy-Making in the Age of Linguistic and Visual Artificial Intelligence: A Theoretical–Applied Analysis with a Case Study of Two Domestic Media Outlets Media Content Policy-Making in the Age of Linguistic and Visual Artificial Intelligence: A Theoretical–Applied Analysis with a Case Study of Two Domestic Media Outlets 1 15 EN Journal Article 2025 02 05 <table> <tbody> <tr> <td> <p>This study aims to evaluate the structural and operational impacts of linguistic and visual artificial intelligence (AI) on media systems, proposing a three-tier governance model to enhance transparency, editorial integrity, and ethical accountability in AI-integrated content ecosystems. The research employs a mixed-methods design combining comparative conceptual analysis, scenario-based sensitivity modeling, and two case studies conducted in Iranian private media organizations. Data were collected over six months through qualitative thematic coding, algorithmic configuration experiments, and expert panel reviews. The study assessed three key dimensions of AI-media interaction: content production, content distribution, and policy-level governance. Quantitative metrics such as semantic error rates, discursive diversity indices, and user complaint frequencies were triangulated with editorial satisfaction surveys and internal policy evaluations to validate the proposed framework. Results indicate that AI-generated content, if unreviewed, leads to a high incidence of factual and semantic inaccuracies (up to 34%), while multi-stage human oversight reduces errors to 3% and improves editorial satisfaction. Engagement-only recommender systems significantly decreased discursive diversity (index dropped to 0.38) and increased cognitive polarization (62%), while hybrid algorithms improved diversity (0.63) and reduced polarization (29%). Media organizations implementing a formal AI ethics charter reported a 64% reduction in content-related complaints and a 27% increase in public trust. The study confirms that internal governance frameworks and ethical transparency significantly enhance audience perception, editorial control, and institutional resilience. The integration of AI into media demands proactive, data-driven, and ethics-oriented governance. The proposed three-tier model offers a scalable framework for managing AI’s risks while fostering editorial responsibility and content authenticity. Institutions that embed human oversight and algorithmic transparency are better positioned to preserve public trust and adapt to the evolving information landscape.</p> </td> </tr> </tbody> </table> https://www.journalfwdmj.com/index.php/fwdmj/article/download/67/58