Lab Innovations’ reports evaluates practical hurdles and ethical questions about AI adoption
Lab Innovations, a UK event for the laboratory industry, has published a report examining how AI is applied in UK laboratories. Produced in collaboration with experts across science and technology, the publication analyses how digital tools are reshaping scientific activity and what this means for laboratories that must balance innovation with responsibility.
Contributors include Dr Marie Oldfield, AI lead at the Institute of Science and Technology (IST), Joan Ward, deputy chair of the IST, Maya Carlyle, principal AI engineer at the National Physical Laboratory and Duncan Lugton, head of Policy and Impact at the Institution of Chemical Engineers. Their combined viewpoints provide insight into how laboratories are approaching AI, from the opportunities it offers to the ethical and organisational questions it raises.
Carlyle said, “There is a risk of hasty AI implementation without sufficient training and explanation of how these tools actually work. Laboratories require clear guidance, skills development and strong governance to ensure the technology adds value rather than undermining scientific standards.”
The report places AI as a topic of intense focus within the laboratory community, describing the institutions keen to explore AI to accelerate discovery and enhance efficiency, while recognising that many are still in the early stages of adoption. There is both enthusiasm and caution as laboratories weigh how to integrate AI into existing practice.
Nicole Hawkins, marketing manager at Easyfairs, said, “The laboratory sector is facing one of the most important transitions in its history. Implementing AI effectively and ensuring scientists maximise these tools will be a significant challenge. Lab Innovations provides a forum where leading experts can come together to examine these questions, share experiences and shape how AI will be applied in practice.”
The report also found that organisations investing in governance and staff capabilities are better positioned to secure long-term benefits from AI while protecting the integrity of scientific work. It positions these insights as a reference point for policymakers and funders who influence the resources available to the sector, as well as for laboratories seeking greater clarity on the frameworks that will guide AI in practice.
