AI in journalism: Opportunity or obsolescence for the fourth estate?

AI’s presence in journalism is not hypothetical. More than 70% of news organizations surveyed across six continents have already adopted generative AI tools for writing, summarizing, or organizing content. While some use it for basic automation - transcriptions, translations, and copy editing - others embed it directly into editorial processes, even generating entire articles or structuring multimedia reports.

The rapid integration of artificial intelligence (AI) into global newsrooms has ushered in what researchers describe as a defining turning point for journalism - one that simultaneously threatens foundational values and unlocks transformative possibilities. More than a wave of automation, AI is reconfiguring how news is produced, who produces it, and how it reaches the public.

This transformation is the focus of a new study titled “The AI Turn in Journalism: Disruption, Adaptation, and Democratic Futures”, published in Journalism (2025). Authored by Tomás Dodds, Rodrigo Zamith, and Seth C. Lewis, the research dissects how AI is not merely a technical tool but a fundamental force reshaping the journalistic field across four key dimensions: technological adoption and hype, shifting power structures, audience dynamics, and the urgent need for educational reform.

Is the AI turn in journalism a moment of disruption or reinvention?

AI’s presence in journalism is not hypothetical. More than 70% of news organizations surveyed across six continents have already adopted generative AI tools for writing, summarizing, or organizing content. While some use it for basic automation - transcriptions, translations, and copy editing - others embed it directly into editorial processes, even generating entire articles or structuring multimedia reports.

The study situates this adoption within the broader context of what it calls an “AI turn” - a paradigmatic shift similar to previous academic and professional shifts like the “data turn” or the “audience turn.” Like those moments, the AI turn challenges long-standing assumptions about what journalism is and how it should function. But AI also raises uniquely existential questions: if machines can produce humanlike narratives and interface directly with users via chatbots or recommendation systems, what remains of the journalist’s role?

Although AI is praised for its efficiency, cost-cutting potential, and scalability, the authors caution against viewing it as a mere upgrade to existing processes. They argue that the hype surrounding AI can obscure the deeper structural realignment taking place, where power, control, and definition of the journalistic profession itself may slip away from journalists and into the hands of tech firms and platforms that build and own the AI infrastructure.

How is AI changing power relations and journalistic norms?

The AI turn has intensified journalism’s dependency on powerful tech platforms, deepening a trend that already disrupted the industry’s financial base in the digital age. With Google integrating AI-based content summaries into its search results, publishers are likely to lose even more referral traffic, further undermining ad revenue models and visibility. Meanwhile, licensing deals with AI firms like OpenAI offer short-term gains but potentially long-term subordination to non-journalistic gatekeepers.

This shift reorders journalism’s historical boundaries. News organizations once defined the information architecture for the public. Now, platforms define access, while AI systems increasingly define interpretation. Generative AI can filter, reframe, and even mimic journalistic content before the journalist’s own words ever reach the audience. This new intermediary role alters the journalist–audience relationship in fundamental ways.

The researchers emphasize that this transformation is not evenly distributed. While elite media outlets and tech-forward newsrooms may shape the discourse, smaller and local news organizations, especially in the Global South, face mounting challenges in resisting platform dependencies and maintaining editorial autonomy. Even as open-source AI alternatives gain momentum, they remain underfunded and fragmented relative to corporate-backed systems.

Yet the study also finds that this moment of upheaval offers strategic opportunity. By reassessing their roles, journalists can reposition themselves not only as content producers but as public educators, watchdogs over AI systems, and guides through a synthetic media landscape flooded with deepfakes, junk content, and algorithmically optimized misinformation.

Can AI coexist with journalism’s democratic mission?

Perhaps the most critical issue explored by the study is AI’s impact on democracy and public trust. Generative AI tools are now widely accessible for use in content creation by marketers, lobbyists, disinformation agents, and newsrooms alike. As synthetic content scales and blurs the boundary between journalism and imitation, audiences face growing uncertainty about authenticity. This fuels news avoidance, misinformation fatigue, and civic disengagement.

AI’s capacity to hyper-personalize content, driven by profiling and behavioral targeting, also risks reinforcing filter bubbles and exacerbating epistemic fragmentation. These developments undermine journalism’s traditional role as a shared public forum that fosters democratic deliberation.

However, the authors argue that AI need not be a purely corrosive force. When deployed thoughtfully, it can support democratic goals by increasing content accessibility, enhancing diversity of voices, and lowering the cost of news production. Tools that translate stories into multiple languages or summarize complex issues into accessible formats have already shown promise.

The key challenge lies in education and empowerment. Journalists, journalism educators, and citizens all face steep learning curves. The study notes widespread gaps in AI literacy among newsroom professionals and journalism educators, with many programs lacking clear instructional frameworks. Without closing these knowledge gaps, the profession risks drifting further from its public-interest mission.

The researchers call for a coordinated response: integrating critical AI training into journalism curricula, fostering open-source innovation, and investing in digital literacy initiatives that prepare the public to navigate AI-infused information ecosystems. Crucially, they urge newsrooms to lead by example, using AI not just to optimize engagement, but to uphold transparency, accountability, and trust.