This study examines the global landscape of AI guidelines in the media industry, analyzing 37 AI guidelines from 17 countries. The research draws on institutional theory and digital inequality concepts to explore how media organizations address the ethical, responsible, and unbiased implementation of AI technologies. Key themes identified include transparency, accountability, fairness, privacy, and the preservation of journalistic values. The study highlights shared principles and best practices, such as the importance of human oversight, explainability of AI systems, disclosure of automated content, and protection of user data. However, the geographical distribution of these guidelines shows a dominance of Western nations, particularly North America and Europe, raising concerns about power asymmetries and isomorphism in AI adoption outside these regions. The study also explores the impact of AI on journalism, including the potential for AI to disrupt traditional roles, raise ethical concerns, and challenge the credibility of news. It emphasizes the need for guidelines that ensure ethical and responsible AI use, including the protection of users, the preservation of journalistic values, and the mitigation of risks such as misinformation and bias. The research underscores the importance of institutionalization in shaping AI adoption in the media industry, highlighting the role of guidelines in promoting ethical standards and accountability. The study finds that media organizations in Western countries are more likely to adopt comprehensive AI guidelines, while non-WEIRD countries often rely on more general or less detailed guidelines. This disparity reflects broader digital inequalities and challenges in AI adoption. The research also highlights the need for localized, nuanced responses to ensure ethical and responsible journalism in a rapidly changing media environment. Overall, the study provides a comprehensive analysis of AI guidelines in the media industry, emphasizing the importance of ethical considerations, institutionalization, and the need for equitable AI adoption.This study examines the global landscape of AI guidelines in the media industry, analyzing 37 AI guidelines from 17 countries. The research draws on institutional theory and digital inequality concepts to explore how media organizations address the ethical, responsible, and unbiased implementation of AI technologies. Key themes identified include transparency, accountability, fairness, privacy, and the preservation of journalistic values. The study highlights shared principles and best practices, such as the importance of human oversight, explainability of AI systems, disclosure of automated content, and protection of user data. However, the geographical distribution of these guidelines shows a dominance of Western nations, particularly North America and Europe, raising concerns about power asymmetries and isomorphism in AI adoption outside these regions. The study also explores the impact of AI on journalism, including the potential for AI to disrupt traditional roles, raise ethical concerns, and challenge the credibility of news. It emphasizes the need for guidelines that ensure ethical and responsible AI use, including the protection of users, the preservation of journalistic values, and the mitigation of risks such as misinformation and bias. The research underscores the importance of institutionalization in shaping AI adoption in the media industry, highlighting the role of guidelines in promoting ethical standards and accountability. The study finds that media organizations in Western countries are more likely to adopt comprehensive AI guidelines, while non-WEIRD countries often rely on more general or less detailed guidelines. This disparity reflects broader digital inequalities and challenges in AI adoption. The research also highlights the need for localized, nuanced responses to ensure ethical and responsible journalism in a rapidly changing media environment. Overall, the study provides a comprehensive analysis of AI guidelines in the media industry, emphasizing the importance of ethical considerations, institutionalization, and the need for equitable AI adoption.