Nieman Lab: Study finds AI is reshaping which skills journalists practice most

A study published in Journalism Practice and examined by Nieman Lab on July 8, 2026 looked at how AI adoption is changing the skill profile of working journalists. The research, conducted by Shangyuan Wu at the National University of Singapore, examines both what journalists may be losing as AI handles more of their baseline work and what new capacities the AI environment is demanding.

What may be declining

The study identifies foundational research skills as the area most at risk. When AI tools can quickly produce background summaries on a topic, the repeated practice of tracking down primary sources, searching databases, and building knowledge from scratch becomes less necessary—and therefore, over time, less sharp. The concern is consistent with findings from an earlier study on ChatGPT use, in which essay writers whose AI-assisted workload increased showed declining independent writing ability over time.

What may be developing

The study points to critical evaluation skills as the capacities that the AI environment is actively demanding. The ability to identify hallucinated information, distinguish between reliable and unreliable sourcing, and catch bias introduced by training data has moved from a secondary concern to a foundational requirement for anyone using AI in a professional writing context.

Why it matters

For journalists, editors, and content professionals evaluating AI in their workflows, this study is a useful frame for thinking about what adoption actually costs over time. The risk is not immediate skill loss—most practitioners will not notice the change in daily work—but gradual atrophy in the areas that AI most readily substitutes for. The implication for editorial teams is that introducing AI tools should be paired with deliberate maintenance of the research and verification practices that AI is most likely to displace.