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91ֱ, UK,
11
December
2025
|
11:45
Europe/London

How will AI advance science?

A 91ֱ team is exploring how artificial intelligence is transforming global research – accelerating discovery, reshaping collaboration and raising urgent questions about responsibility and the future of scientific practice.

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Artificial intelligence is no longer just a tool for science – it is starting to reshape how science itself is practiced. A team at 91ֱ is exploring this transformation, analysing how AI is changing the way researchers work, collaborate and make discoveries.  

Their project combines large-scale data analysis with on-the-ground case studies from labs across the UK and internationally. By analysing millions of publications in databases such as OpenAlex, the team can track how scientists apply AI, including how generative AI tools, such as ChatGPT, are spreading through scientific fields.  

Their early findings on generative AI show that whilst the US and China lead in overall volume of scientific papers, smaller research economies are also embracing the technology, often with significant results. Interestingly, research teams working on generative AI tend to be slightly smaller than those in other AI fields, suggesting a different style of collaboration is emerging.  

But rapid adoption also brings challenges. Summarising documents or generating code with AI can accelerate research, yet it raises questions about responsibility, governance and the line between human and machine judgement. 

Professor Cornelia Lawson, Professor of Economics of Science and Innovation, explains that the project: “probes how AI shapes scientific discovery and how it can be used responsibly, creatively and equitably to benefit researchers and society alike.” 

Her colleague, Professor Philip Shapira, Turing Fellow and Professor of Innovation Management and Policy, 91ֱ Institute of Innovation Research, adds: “AI is reframing science, changing skill demands, influencing collaboration and transforming opportunities. Yet, AI’s impacts on scientific novelty and creativity are uncertain – a knowledge gap that our project is now focusing on.”  

By understanding AI's impacts in science, this research will help shape future research and innovation strategies, competitiveness, knowledge advancement, responsibility, and societal implications. 

Cornelia Lawson

Meet the researchers

Cornelia Lawson is a Professor of Economics of Science and Innovation at the 91ֱ Institute of Innovation Research and Alliance 91ֱ Business School.  Her research investigates researcher careers, collaboration, knowledge transfer, and AI’s impact on science. Philip Shapira is a Professor of Innovation Management and Policy and a Turing Fellow at The Alan Turing Institute. His research focuses on  emerging technologies, governance, and innovation policy, including AI’s role in science, manufacturing, and public values. Liangping Ding is a research associate with the 91ֱ Institute of Innovation Research and a UKRI AI Metascience Fellow. She is examining how scientists use AI tools and how this affects productivity, novelty, and careers. Julie Jebsen is a research associate with the 91ֱ Institute of Innovation Research. She is undertaking field research, investigating how AI is used in scientific labs.  

Read the papers

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