A growing shift is underway in how scientists approach complex problems, with artificial intelligence increasingly stepping in as a collaborative tool rather than just a support system. OpenAI has detailed this transition in a new report, highlighting how AI systems such as ChatGPT are helping researchers across mathematics, physics, chemistry, and biology move faster and work more efficiently.
The 20-page report explains that scientists are now using AI for tasks such as reviewing academic literature, interpreting data, and planning experiments. OpenAI noted that strengthening AI’s research capabilities could significantly boost discovery and productivity across science and engineering.
The report, shared exclusively with a digital news platform, includes anonymised usage data showing that millions of scientists, engineers, and mathematicians already rely on AI for scholarly work. This includes drafting scientific content, debugging code, and designing experiments. OpenAI’s analysis found that most researchers currently use AI for writing and communication, while fewer depend on it for advanced analysis and calculations. This gap, the company said, points to clear opportunities for deeper AI integration in research workflows.
According to OpenAI, anonymised ChatGPT conversations between January and December 2025 showed that average weekly messages on advanced science and mathematics topics grew by about 47 percent year-on-year. In absolute terms, message volumes rose from 5.7 million to nearly 8.4 million. By January 2026, nearly 1.3 million weekly users were discussing advanced science and mathematics topics on the platform.
“AI is increasingly being used as a scientific collaborator, and we’re seeing its impact grow in real research settings. More researchers are using advanced reasoning systems to make progress on open problems, interpret complex data, and iterate faster in experimental work. That usage has been growing quickly over the past year, and the results are starting to show up across fields. We’re still early, but the pace of adoption and the quality of the work suggest science is entering a new acceleration phase,” said Kevin Weil, VP of OpenAI for Science.
This approach aligns with initiatives such as OpenAI for Science, which aims to connect researchers with AI tools that can speed up workflows from literature analysis to modelling and simulation. OpenAI said its long-term goal is to build systems that fit naturally into scientific practice and help unlock discoveries that might otherwise take years.
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