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A recent study by Wiley highlighted variations in AI adoption among researchers across disciplines and career stages.
The findings indicate that professionals in computer science (44%) and medicine (38%) fields and those earlier in their careers (39%) are more inclined to adopt AI early. In contrast, those specializing in life sciences and those late in their careers (41%) tend to be more cautious about integrating AI into their work. Roughly two-thirds of mid-career researchers want to be early or average adopters of AI technology.
In addition, AI adoption varies across regions. Researchers in China (59%) and Germany (57%) are leading in integrating AI into their work, compared to the global adoption rate of 44%. Additionally, 57% of early career researchers have already used AI in their work.
The study was based on insights from nearly 5,000 researchers worldwide in 2024, Wiley said.
Barriers to AI adoption and current use
The study identified the lack of clear guidance and training as major barriers to wider AI adoption, with 63% of researchers citing these as challenges. As a result, AI usage remains concentrated on a few core tasks, particularly among late-career researchers (66%), according to the ExplanAItions study.
Despite these challenges, researchers expect a rapid expansion in how AI is employed throughout the research process. Notably, many researchers already recognize AI’s potential with a majority stating that the technology outperforms humans in more than half of the 43 use cases evaluated in the study.
Concerns about AI models
While interest in AI remains high, concerns about the models persist. About 81% of researchers expressed one or more concerns about AI, with ethical issues (54%), lack of transparency in AI training and facility (46%), accuracy (51%), and data security or privacy (47%) ranking as the most common. This highlights the significant obstacles researchers face in increasing their use of AI, the report said.
Regional differences also emerged, with researchers in Japan (85%) and China (84%) reporting heightened concerns about the AI models. The study also found that social sciences researchers (86%) and researchers in the academic sector (83%) cited concerns regarding AI’s role and implications in their fields.
Where AI outperforms humans — and where humans shine
AI is recognized for excelling in tasks requiring speed, accuracy, and processing large datasets. In those instances, the researchers “recognize that AI can save time, handling monotonous and repetitive work,’’ the study found.
However, human expertise remains superior in areas requiring intuition, judgment, creativity, and complex problem-solving.
“We’ve heard researchers loud and clear,’’ said Jay Flynn, Wiley executive vice president and general manager of research and learning, in a statement. “We’re committed to supporting authors as they navigate this transformation and will offer guidance on how to use generative AI tools with greater confidence.”