The University of Manchester media team has posted a nice piece on work (with Cornelia Lawson, Liangping Ding & Julie Jebsen at the Manchester Institute Of Innovation Research) probing how will AI advance science? (aka The “AI in the Lab” Project).
The original piece is at https://www.manchester.ac.uk/about/news/how-will-ai-advance-science/.
PS. The photo at the end of the piece is from our recent AI in the Lab international workshop with our European partners.
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How will AI Advance Science?
Manchester, UK, 11 December 2025
A Manchester 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.
Artificial intelligence is no longer just a tool for science – it is starting to reshape how science itself is practiced. A team at Manchester 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, Manchester 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.
Meet the researchers
Cornelia Lawson is a Professor of Economics of Science and Innovation at the Manchester Institute of Innovation Research and Alliance Manchester 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 Manchester 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 Manchester Institute of Innovation Research. She is undertaking field research, investigating how AI is used in scientific labs.
Read the papers
- Rise of Generative Artificial Intelligence in Science.
- Generative AI in Science: Applications, Challenges, and Emerging Questions.
- Tracking developments in artificial intelligence research: constructing and applying a new search strategy.
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Philip Shapira 