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A recent study by Wiley highlighted the variation in AI adoption between researchers across academic and career stages.
The findings show that the fields of computer science (44%) and medical professionals (38%), as well as early career stages (39%) tend to adopt AI early. In contrast, people who specialize in life sciences and later careers (41%) tend to be cautious about integrating AI into their work. Approximately two-thirds of medium-sized researchers want to be early or average adopters of AI technology.
Furthermore, AI adoption varies from region to region. Chinese researchers (59%) and Germany (57%) are leading the way in integrating AI into their work, compared to a global adoption rate of 44%. Additionally, 57% of early career researchers already use AI for 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 identifies the lack of clear guidance and training as a major barrier to wider AI adoption, with 63% of researchers cited these as challenges. As a result, AI use remains concentrated on several core tasks (66%), especially among late researchers.
Despite these challenges, researchers hope for a rapid expansion in how AI will be adopted throughout the research process. In particular, many researchers already recognize the potential of AI, saying the technology outperforms humans in more than half of the 43 use cases evaluated in the research.
Concerns about AI models
While interest in AI remains high, concerns about the model persist. Approximately 81% of researchers expressed one or more concerns about AI, including ethical issues (54%), lack of transparency in AI training and facility (46%), accuracy (51%), and data security or As the most common ranking for privacy (47%). This highlights the important obstacles researchers face when increasing the use of AI, the report said.
Regional differences also emerge, with Japanese researchers (85%) and China (84%) reporting growing concerns about AI models. This study found that social science researchers (86%) and academic department researchers (83%) cite concerns about their role and implications in the field of AI.
Where AI surpasses humans – and where humans shine
AI is recognized for its superiority in tasks that require speed, accuracy, and processing of large data sets. In these examples, researchers “recognize that AI can save time and handle monotonous, repetitive tasks,” the study found.
However, human expertise remains excelling in areas that require intuition, judgment, creativity and complex problem solving.
“We’ve heard researchers loudly and clearly,” said Jay Flynn, executive vice president and general manager of research and learning at Wiley, in a statement. “We are committed to helping you support us in navigating this transformation and providing guidance on how to use generator AI tools with more confidence.”
