Welcome to our latest roundup of updates, insights, and resources exploring the use of Artificial Intelligence in research and across the research sector. This roundup covers the latest news in AI, key developments on AI’s impact in research, policy, institutional stories and the voices of our communities.
News & policy updates
Aston University and the University of Leeds win £3.4m for artificial intelligence tools researcher development network.
The funding will support a four year project to create a researcher development network focused on the use of publicly available AI tools in doctoral research. As well as examine how tools like ChatGPT and Microsoft Copilot are being used (or could be used) by doctoral researchers, their supervisors, examiners, and support staff. The project will engage with stakeholders to understand how AI tools are adopted, innovate, and what challenges arise.
Research infrastructure & national priorities starting to shift.
Researchers at the University of Sheffield and the Alan Turing Institute have published a new framework for building AI that learns from multiple types of data, not just vision and language as most AIs currently do. The new framework is designed to guide the real world deployment of AI systems that combine different types of data like text, images, sound, and sensor readings.
For UK academics the message is clear, future funding and collaboration opportunities will favour projects that focus on deployable, real world AI systems, integrate multiple data types, embed trust, safety, and have ethics at the core.
The University of Lincoln chosen to lead project using artificial intelligence (AI) in defending the country.
The £1m research contract was awarded by the Ministry of Defence. The university of Lincoln will lead a consortium of seven UK universities, including Oxford and Cambridge, working on using AI to support the government and military in national security scenarios. It’s clear what’s being emphasised in AI research currently is “use” and “impact”. With the government framing AI as an economic driver, research proposals around productivity, growth, and public service transformation are the ones gaining traction.
Research with clear pathways to deployment, measurable impact, and collaborations with industry or public services will be more competitive and more likely to be applied, scaled and embedded in sectors (health, energy, education and public services).
UK Research and Innovation Partners Deliver UK AI Research Symposium.
The inaugural UK AI Research Symposium took place at Northumbria University last month, the event brought together researchers from a variety of academic disciplines, all working within the AI community. The event forged links between theoretical research and real world applications to benefit society.
Areas of focus included people centred AI, AI in law enforcement, public sector governance and digital education, as well as emerging areas of research in environmental impacts of AI, educational use of AI, and the impact of AI on the creative sector. Again, signalling a clear shift in focus for AI research in the UK: not just advancing capabilities, but emphasising impact, deployment, and societal benefit.
University of Durham launches international research centre to explore impact of AI and algorithms on society.
Durham University has launched the Leverhulme Centre for Algorithmic Life (CAL), a major international research hub focused on how AI and algorithms are changing society. It brings together global partners including universities in York, Edinburgh, Amsterdam and the USA. With £10 million in funding, the projects aim is to understand how algorithmic technologies shape lives, decisions, and societies. The societal focus means that research proposals which link AI with real world impact, governance, ethics and societal change will be well positioned in this emerging landscape.
Staff development lagging in universities and FE despite rising AI use.
According to Jisc’s “Staff Perceptions of AI 2025” survey, only about 37% of HE institutions have delivered staff training on AI, and 44% in FE. Though most have some kind of policy, many staff feel unclear about what policies mean in practice. Governance gaps appear between policy statements and lived experience. Artificial intelligence
Assuring academic quality in the age of AI is a growing concern for Quality Assurance agencies.
The European University Association argues that as AI becomes widespread, quality assurance bodies need to adapt new methods, checks for academic integrity, training for staff, and strategies for trust. This becomes central for accreditation and reputational quality. European University Association
University of Exeter launches new research centre focused on investigating how artificial intelligence (AI) affects society.
Key themes from the launch looked at how AI impact’s identity and labour, especially in the Global South. The political dimensions of AI, including its role in conflict, regulation, and resistance. The initiative responds to growing awareness that AI is deeply embedded in society affecting people’s lives, work, rights, communities.
Switzerland launches national Large Language Model (LLM) to provide an alternative to the likes of ChatGPT, Llama and DeepSeek.
Designed by leading Swiss universities, the Apertus LLM is comparable to Meta’s Llama 3 model from 2024. Since then, Meta and other rivals have produced more advanced versions, but the Swiss say their system is aimed at general users in favour of a safer and more accessible AI system for scientific researchers and commerce.
In-case you missed it:
Imperial College plans new AI campus
Investment in British AI companies hits record levels
Why Language Models Hallucinate
Jisc AI in Research Community Meet Up
This month Jisc held its first online community meetup for the research community. It was a great conversation. The meetup brought together academic professionals to discuss the ethical implications and practical challenges of using AI tools in research. Key topics included concerns about using AI in peer review processes, legal risks associated with data and AI tools, and the need for clear guidance for doctoral researchers.
Participants emphasised the importance of sector wide agreement on appropriate AI use, ethical practices, and addressing systemic issues in academic labour that drive reliance on AI tools. A summary of the meet up will be published and we welcome you to join us for the next meet up on Monday the 3rd of November 15:30-16:30.
Extra Considerations
Data Transparency and Bias:
As AI tools become more integrated into research, there’s growing emphasis on understanding how datasets are built and what biases they may contain. Transparent data practices are essential to ensure research findings remain fair, reproducible, and trustworthy
Human–AI Collaboration:
The focus is shifting from replacement to partnership. Successful researchers are learning how to “co-work” with AI, using it to generate ideas, automate analysis, or simulate scenarios, while retaining human oversight and intellectual ownership.
Skills and Literacy:
AI literacy is now becoming a key academic skill. Researchers and educators need to understand not just how to use AI tools, but how to question their outputs, evaluate reliability, and integrate them ethically into their work.
Find out more by visiting our Artificial Intelligence page to explore publications and resources, learn more about our communities and sign up for our AI Literacy training.
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Get in touch with the team directly at AI@jisc.ac.uk