UKRI has committed up to £60 million to two new AI research labs, SOFAIR and BOLD, led by UCL and the University of Oxford and funded through the Engineering and Physical Sciences Research Council (EPSRC). For grant applicants, the announcement signals a shift toward fundamental, open-source AI research, cross-institution consortium bidding, and a staged, assessment-gated funding model that is likely to shape future UKRI AI calls across all seven research councils.
UKRI’s AI research labs are strategic, multi-year research centres — the first major investment released under UKRI’s AI Strategic Framework — built to fund high-risk, high-reward fundamental AI research rather than applied product development. The two labs were announced on 23 June 2026, timed to coincide with what would have been Alan Turing’s 114th birthday.
- What are UKRI’s new AI research labs?
- Why did UKRI double the investment to £60 million?
- What does this mean for grant applicants?
- How does this fit UKRI’s cross-council AI strategy?
- Frequently asked questions
- Implications and outlook
What are UKRI’s new AI research labs?
UKRI’s two new labs are the Science of Fundamental AI Research (SOFAIR) Lab, led by UCL, and the British Open-ended Learning and Discovery (BOLD) Lab, led by the University of Oxford. Both are funded through EPSRC, the UKRI council responsible for engineering and physical sciences, and both work across consortium partners rather than a single institution.
SOFAIR brings together UCL with the universities of Cambridge, Oxford and Edinburgh to develop next-generation open-source AI architectures that can run on widely available hardware, reducing dependence on a small number of proprietary model providers. It is led by Professor David Barber of UCL. BOLD, led by Associate Professor Jakob Foerster of Oxford, works with UCL and Imperial College London on new learning paradigms — human-centred AI, embodied systems and learning without vast centralised compute.
| Feature | SOFAIR Lab | BOLD Lab |
|---|---|---|
| Lead institution | UCL | University of Oxford |
| Lead investigator | Professor David Barber | Associate Professor Jakob Foerster |
| Consortium partners | Cambridge, Oxford, Edinburgh | UCL, Imperial College London |
| Core focus | Open-source AI on accessible hardware | New learning paradigms, embodied AI |
| Initial funding released | ~£8 million | ~£8 million |
| Doctoral training ring-fence | £2 million (min. 10 students) | £2 million (min. 10 students) |
Why did UKRI double the investment to £60 million?
UKRI’s original plan committed £40 million to a single AI research lab. The final announcement doubled the number of labs to two and lifted total committed funding to up to £60 million — a signal that the review panel judged the applicant pool strong enough to fund parallel, competing research directions rather than consolidate around one.
Each lab initially receives around £8 million, with the remainder of its allocation released only after an assessment in autumn 2026. This staged, gated funding model — rather than a single upfront grant — is itself a departure from how UKRI has typically structured large capital-style research investments, and it is a detail every institution bidding into future rounds should note.
What does this mean for grant applicants?
For institutions and principal investigators watching UKRI’s AI funding pipeline, four practical signals stand out:
- Consortium bids are favoured over single-institution proposals. Both labs span three to four universities, reflecting UKRI’s preference for pooled expertise over isolated centres of excellence.
- Fundamental, “blue-sky” research is explicitly back in favour. EPSRC’s framing prioritises foundational questions — new architectures, new learning algorithms — over applied deployment work, reversing some of the recent emphasis on near-market translation.
- Doctoral and early-career funding is ring-fenced, not discretionary. Each lab must support a minimum of ten doctoral students from a dedicated £2 million allocation, giving PhD applicants and postdocs a concrete, quantifiable funding route rather than a vague promise of “opportunities.”
- Continuation funding is now conditional on a mid-point review. Applicants should expect future large AI awards to build in an autumn-style assessment gate before releasing full committed funding, rather than disbursing the full sum at award.
Open-source commitments and spin-out support are also written into both labs’ remits, so institutions preparing future bids should be ready to demonstrate a route to commercialisation and public dissemination of tooling, not only publication output.
How does this fit UKRI’s cross-council AI strategy?
EPSRC administers the SOFAIR and BOLD awards, but the labs sit inside a wider, cross-council AI programme. UKRI comprises seven research councils, and the AI Strategic Framework explicitly positions AI as a cross-cutting priority rather than an EPSRC-only remit. The Science and Technology Facilities Council (STFC) — best known for its Hartree Centre, which provides supercomputing and applied AI infrastructure to UK researchers and industry — sits alongside EPSRC as part of that same seven-council structure, underscoring that compute infrastructure and fundamental AI research are being coordinated as complementary strands of one strategy rather than funded in isolation.
Professor Charlotte Deane, Senior Responsible Owner for the UKRI AI Programme and Executive Chair of EPSRC, described the labs as backing “the bold, high-reward ideas that can shape the future of AI” — language that maps directly onto UKRI’s broader AI strategy documents, which call for regional clusters, sovereign compute capability and closer links between fundamental research councils and applied infrastructure providers such as STFC and the Alan Turing Institute.
Frequently asked questions
What is the UKRI AI strategy plan?
UKRI’s AI strategy sets out a plan to turn the UK’s research strengths into economic advantage by backing fundamental AI research, regional innovation clusters and sovereign AI capability. The SOFAIR and BOLD labs are described as the first major investment released under this framework, with further AI calls expected to follow the same fundamental-research emphasis.
How much funding did UKRI commit to the new AI labs?
UKRI committed up to £60 million across the two labs, doubling an original £40 million single-lab plan. Each lab receives an initial tranche of roughly £8 million, with the remaining funds released after an autumn 2026 progress assessment.
Can researchers outside UCL and Oxford apply for lab funding?
The two labs are led by UCL and Oxford with named consortium partners, so direct lab leadership is fixed. However, doctoral studentships, postdoctoral posts and collaboration opportunities are expected to open as the labs recruit, and researchers should monitor EPSRC and UKRI funding-opportunity pages for associated calls.
Which universities lead UKRI’s new AI research labs?
UCL leads the SOFAIR Lab with Cambridge, Oxford and Edinburgh as partners; the University of Oxford leads the BOLD Lab with UCL and Imperial College London as partners. Both labs also engage with the Alan Turing Institute and UKRI’s existing AI research hubs.
Implications and outlook
For research administrators drafting institutional AI strategies, the SOFAIR and BOLD awards are a useful template for what UKRI now expects from a competitive large-scale AI bid: multi-institution consortia, an explicit open-source or public-good deliverable, a ring-fenced doctoral-training component, and acceptance of a staged funding gate rather than a single lump-sum award.
The autumn 2026 assessment point is worth diarising directly — it will be the first public test of whether UKRI’s gated model releases the remaining funds smoothly or triggers a public renegotiation, and either outcome will inform how future large AI calls from EPSRC, and potentially jointly with STFC’s compute-infrastructure remit, are structured. Institutions preparing bids for the next round of UKRI AI funding should treat this announcement as the current baseline for what “fundable” fundamental AI research now looks like in the UK.