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In Journalism Practice, Emma Verhoeven and Sarah Van Leuven examined generative AI’s impact on journalism employment and found that rather than replacing journalists, it reshapes skills via reskilling and deskilling.

Generative AI is beginning to take over parts of journalistic work, from spotting stories to producing content, raising both hopes and anxieties about the future of the profession. This study looks at how it is changing work conditions and job security through interviews with key actors in newsrooms in Belgium. The broader picture is more complex than simple narratives of disruption, as long-standing economic pressures and newsroom practices also shape these changes.

In newsrooms, AI is settling into everyday workflows without overturning them. Large media groups have built dedicated teams and secure systems, weaving AI into content management tools that suggest headlines, summaries, or handle transcription and translation. Smaller outlets move more loosely, often relying on free tools, while a few draw firm ethical lines and restrict AI to research support. In general, automation remains limited in scope and tightly supervised, even if that supervision is uneven in practice.

The authors found that fears of widespread job loss have eased as AI’s limits have become clearer. Journalists mostly use it to offload repetitive work, which saves time but does not yet translate into measurable efficiency gains. Managers do not rule out small staffing adjustments over time, though not on a large scale. The more immediate pressure falls on freelancers, whose roles can be quietly reduced. Fully automated publishing exists only in narrow, data-driven areas like sports results or real estate listings, where structured inputs make automation feasible and where such coverage would otherwise not necessarily exist.

At the same time, AI is creating new roles and reshaping existing ones. News organisations are appointing editors with hybrid responsibilities, bridging editorial judgment and technological implementation. In some cases, journalists specialise in crafting prompts and refining how AI tools are used, a task framed less as technical work than as an extension of editorial thinking. These developments open new career paths but also deepen inequalities between large, well-resourced organisations and smaller outlets struggling to keep up.

Nevertheless, certain skills are losing ground. Routine language tasks, basic editing, and parts of distribution are increasingly automated, while expectations shift toward creativity, judgment, and adaptability. The picture that emerges is not one of sudden disruption but of gradual reorganization, shaped as much by long-standing economic pressures and newsroom hierarchies as by the technology itself.

Stepping back, the study suggests that generative AI is not transforming journalism as dramatically as often claimed. Its effects remain modest and uneven, more an extension of long-running digital shifts than a break with them. Direct job losses are rare, but change seeps in through hiring freezes and unfilled vacancies, quietly narrowing opportunities over time. Skills tied to judgment, verification, and human storytelling gain importance and journalists lean into this distinction, emphasising what machines cannot replicate.

The research also uncovered that old tensions persist. The promise of freeing up time for deeper reporting coexists with fears of cuts and heavier workloads, much as it did a decade ago. For some, especially freelancers and newcomers, the risks are sharper. Access to training and tools is uneven, competition intensifies, and entry-level pathways may shrink as basic tasks disappear. Newsrooms respond by pushing staff toward new skills or roles, though this adaptation depends heavily on resources.

Verhoeven, E., & Van Leuven, S. (2026). Between Anticipation and Impact: Assessing Generative AI’s Influence on Journalistic Labor and Employment. Journalism Practice, 1–17. https://doi.org/10.1080/17512786.2026.2692441