Artificial Intelligence in Journalism: A Narrative Review of Opportunities, Challenges, Ethical Tensions, and Human-Machine Collaboration

Artificial Intelligence (AI) is changing the practices of journalism around the world, which influence how news is gathered, produced, and disseminated. This review synthesizes theories, empirical, and other literature to explore the multidimensional impact that AI has on journalistic workflows and values. This review centered on 81 core sources published between 2015 to 2024, examining AI’s affordances, including automation of routine reporting, data mining and audience personalization. The paper also assesses the emerging risks such as algorithmic bias, erosion of editorial transparency, and the popularity of deepfakes in the media. Guided by Human–Machine Communication (HMC) frameworks, Actor-Network Theory, and affordance theory, this review submit that AI is a collaboratived partner rather than a competitor to human journalists. Case examples from newsrooms worldwide (e.g., Associated Press, Washington Post, ICIJ) show both promise and issues in AI integration to the practice of journalism. The paper also addresses the ethical tensions arising from AI-generated content, newsroom accountability, and evolving public trust in machine-assisted reporting. The paper offers future directions that highlight seven key areas: advancing deepfake detection tools, creating of AI ethics guidelines, advocating for the AI training in journalism education, and bridging technological gaps between large and smaller newsrooms. It concludes by hammering on maintaining human editorial oversight and democratic values as AI is growingly augmented in journalistic practice. This paper, therefore, offers a timely and interdisciplinary contribution to media scholars, technologists, and newsroom leaders who are embracing the future of AI-driven journalism.