The Evolving Journalist in the AI Era

By: Darian Hale

Artificial intelligence has found itself in most, if not all, professions, from its usage in the medical field to the AI tools being used to determine financial reports.

But now this same technology is finding its way into newsrooms. Major news organizations have already started using AI in everyday workflow tasks like metadata enrichment, headline suggestions, and content distribution (Simon 2024). (But what does this usage of AI and AI tools mean for the role of journalists?)

For years journalists have evolved alongside technology, adapting it as an extension of their work rather than a replacement. From typewriters to digital editing software, each form of innovation in technology has been adopted into the process of writing and reporting without posing a threat to the journalistic role.

However, AI is making the question of what it means to be a journalist reevaluated. With so much disinformation on the rise, along with the mass-production of content, that appears to be plausible but is quite the opposite. The public is already becoming more hesitant to see what is and is not authentic.

This confusion places new pressure on journalists to do what they have always done but differently, not only report and prove but ensure that truth can be trusted in an environment where AI is shaping both the message and medium. This growing uncertainty is posing the question of what parts of journalism must remain distinctly human?

Tasks like drafting stories, analyzing data, and distributing content have started to leave journalistic roles of human oversight.

[With this and other tasks being automated, the profession loses some authority, but this doesn’t mean taking all authority. It only means that journalists will have to move to a different territory and the existential look into redefining their roles as journalists. This coincides with how journalists should be using AI as a tool to support human expertise, rather replacing it.

Allowing journalists to focus on skills that machines cannot replace while using them to verify false information. In this sense journalists are no longer just conveyers of information but rather reshape themselves as ethical gatekeepers, responsible for not only delivering but calling out and verifying.] Diving into how AI could be used to inform the public, by spotting disinformation and what it means to use AI ethically (Møller 2024).

The New Responsibility of Journalist in the AI Era

To understand how journalism is evolving, it’s important to look at what AI is doing in the newsroom. Today, AI systems write short stock-market summaries, recommend headlines, and optimize article placements on websites. These tools are speeding up production and changing the rhythm in newsrooms.

According to Simon (2024), AI-driven automation has created what is known as an “invisible assistant” especially in the field of editorial departments. These non-visible counterparts are helping journalists save time while shaping what stories are chosen and how they are presented.

What poses the risk of this is the line between assisting and directing? If journalists lose sight of their judgmental role in deciding what the public truly needs to know. This danger is felt by many journalists regarding future AI in the newsroom.

As Dr. Tomas Dodds, an assistant professor at the University of Wisconsin-Madison, studies journalism ethics and technology described that AI’s role in journalism is cognitive offloading. This cognitive offloading is a process where human skills, like writing headlines or fact-checking, are transferred to AI.

According to Dr. Dodds “The ability to write headlines is not enough; journalist must now focus on curating, analyzing and making ethical decisions.” Dodds explained that journalists who fail to understand how AI tool’s function risks reproducing their errors or biases.

The role of the modern journalist now is not only to tell stories but also to interpret how those stories are created and that the audience can trust them. Despite these ethical expectations, few newsrooms have formal guidance on how AI should be used.

According to the Thomas Reuters Foundation Insights Report (Radcliffe 2025), a survey done on the lack of newsroom policies found that only 13 percent of journalists reported they had an AI policy.

This leaves most to “navigate adoption largely on their own” (p. 26). From this a vacuum that is created that is inconsistent to standards and resulting in “AI fails” (p.25) which will become more common and can undermine public trust. Dodds and Radcliffe reinforce the call of explicit disclosure norms. In its core, if journalists serve as gatekeepers, they must first establish a clear journalistic framework that controls the use of AI.

Because most journalists are unfamiliar with the practical application of AI in the newsroom. This deployment of AI in the newsroom is a new frontier for most journalists; newsrooms lack direction and confidence in handling AI. With half of the editors expressing a neutral stance on AI integration, this also coincides with a similar plight. That being the training when it comes to AI integration. More than half of journalists said that they were self-taught, on the integration of learning from online sources or workshops (Radcliffe 2025). This environment mirrors a problem that De Lima-Santos and Ceron (2021) describe as a “technological divide.” From this divide larger well-funded organizations benefit from AI innovation while smaller local outlets struggle to keep the peace. Out of this division Dodds explained that two types of journalists are created “There are journalist that are empowered to innovate responsibly with AI and those left vulnerable to its flaws.”

The ethical risk goes beyond workflow inconsistencies. Over half of Radcliffe’s respondents expressed concern that increased reliance on automation may diminish creativity, originality, and critical thinking skills a sentiment shared by other researchers, that perhaps worries that excessive automation can erode the interpretive depth that allows audiences to trust journalists (Møller 2024).

Similarly, Dodds expressed that journalists must interpret the stories to ensure that the audience can trust them. The first step into this is verification.

Synthetic text, images, and audio flood social feeds. The jobs shift from proving what happened to showing how we know it happened. In practice, this means disclosing sources and methods, having a chain-of-custody for documents, reverse-image searches, archival comparisons, and corroborating records; it also means labeling when and how AI assisted and where a human verified (Møller, 2024: Radcliffe, 2025).

Where we go from implementation, creation, and navigating AI in the newsroom.

The next phase for journalism lies in how well professionals balance innovation with integrity. The AI turn is unlike any pervious wave of digital change, because it forces the identity of journalism to shapeshift. For years, the story of technology in newsrooms has been accelerating “the hamster wheel,” as Dodds calls it where speed and quantity often can eclipse accuracy and reflection.

The arrival of AI makes that race a little more competitive while offering what Dodds labels “an off-ramp”: a chance to pause, reassess and apply technology more meaningfully. This balance between acceleration and reflection defines the current moment in journalism. An AI turn is a breaking point.

A continuing concern is which journalistic responsibilities cannot be delegated to AI? Møller (2024) reinforces this view, making the claim that AI cannot replicate interpretation, context, and the moral responsibility that defines journalism. Journalists will become not simply reporters, or content creators, but verifiers explaining how.

Yet as automation expands, structural challenges arise. AI’s integration grows depending on the very technological companies supplying the tools (Dodds 2025).

The threat of this also echoed from the advantage that major platforms now control the flow of both the data and the audience. But the counter to that is one thing alone, and that is education and empowerment.

Education Empowerment and learning tools. A bridge must be built between newsrooms and academic institutions. Collaboration between journalists and researchers is imperative for developing clarity with AI use and supporting crucial journalism. Both Radcliffe (2025) and Hermida (2024) note that AI should not be treated as specialized only for data journalists.

But competency is taught alongside fact-checking, verification, media law and ethics. Universities and media must develop partnerships that foster continuous learning, allowing working journalists to access ongoing training and academic researchers to study AI’s real newsroom impact. In this sense the future of journalism as Dodds explains “It will resemble a model of classroom and newsroom where both experimentation and reflection can occur side by side.” This partnership also has a broader civic function.

When academics and reporters forge AI’s role in society it creates a ethical participation of AI in the newsroom and public trust. As Møller (2024) identifies that trust cannot thrive in isolation, there must be communication consistently across institutions. By working together scholars and journalists promote both ethical journalism and accountability.

Coming back to the main answer to this, all that has been reinstated is audience trust. Verification is no longer a backstage process; it is a public performance of true credibility. When journalists show that AI can be used responsibility, audiences can feel more comfortable and inclined to trust (Dodds’s interview 2025).

The Human Side of AI

In my interview with Dr. Dodds, he reflected on how this technological shift demands not only skill but also self-awareness.

“The ability to write just simply is not enough anymore,” he said, “Journalist must now focus on the analyzing, no AI will never replace journalist, but it will replace journalist who will refuse to learn how to use it responsibly.”

Dodds also described that journalists will be interpreters of systems, “Audiences will not just ask why this happened, but how did a machine have a hand in telling the story, "Said Dodds.

Redefining credibility is the task for the next generation. Our conversation was concluded with a reminder that tied everything together from the sources in this article. “The future of journalism depends on people who can think critically with technology not against it.”

Conclusion.

Journalism is in an area where it is torn and reshaped. What Dodds calls “a constitutive moment.” The path forward now will depend on the adaptation of journalism to deepen human oversight.

Working together, journalists, educators and technologists establish frameworks for Ai use that uphold ethical journalism and reinforce accountability to the public. AI can amplify efficiency, but only ethics can preserve trust. “Technology will keep changing as it always has; what must not change is the responsibility to tell the truth.” Said Dodds, with this being at the forefront.

The evolving journalist in the AI era is neither obsolete nor left a stray. They are above all accountable to the facts, to the public and promise that truth itself, however assisted by machines. Will remain human at its core.

Sources & References: De-Lima-Santos, M.-F., & Ceron, W. (2021). Artificial intelligence in news media: Current perceptions and future outlook. Journalism and Media, 3(1), 13–26. https://doi.org/10.3390/journalmedia3010002

De-Lima-Santos, M.-F., & Ceron, W. (2021). Artificial intelligence in news media: Current perceptions and future outlook. Journalism and Media, School of Communication, University of Navarra, 3(1), 13–26. https://doi.org/10.3390/journalmedia3010002

Dodds, T., Zamith, R., & Lewis, S. C. (2025). The AI turn in journalism: Disruption, adaptation, and democratic futures. Journalism, 0(0). https://doi.org/10.1177/14648849251343518

Hermida, A. (2024, September 26). From automata to algorithms: A jobs-to-be-done approach to AI in journalism. Revistas.ucm.es; Complutense University of Madrid. https://revistas.ucm.es/index.php/ESMP/article/view/97746/4564456570496

Interview with Tomas Dodds. (2025, October 9). Conducted by Darian Hale.

Lynge Asbjørn Møller, M., Skovsgaard, M., & de Vreese, C. (2024). Reinforce, readjust, reclaim: How artificial intelligence impacts journalism’s professional claim. Journalism, 26(7). https://doi.org/10.1177/14648849241269300

OpenAI. (2025). ChatGPT. https://chatgpt.com

Radcliffe, D. (2025). TRF INSIGHTS journalism in the AI era: Opportunities and challenges in the Global South and emerging economies. Thomson Reuters Foundation. https://www.trust.org/wp-content/uploads/2025/01/TRF-Insights-Journalism-in-the-AI-Era.pdf

Simon, F., Rasmus, K., Nielsen, R., & Fletcher, R. (2025). Generative AI and news report 2025: How people think about AI’s role in journalism and society. Reuters Institute for the Study of Journalism. https://reutersinstitute.politics.ox.ac.uk/sites/default/files/2025-10/Gen_AI_and_News_Report_2025.pdf