CASRAI Dictionary

Category: Policy & Funding News

Reporting and briefings on external policy, regulatory, and funder developments affecting the research community worldwide.

  • Text and Data Mining Copyright Exception: The UK’s 2026 Decision

    The UK’s text and data mining copyright exception currently permits copying protected works for computational analysis only where the purpose is non-commercial research, under Section 29A of the Copyright, Designs and Patents Act 1988. In March 2026, the UK government confirmed it will not introduce a broader, opt-out-based exception for commercial AI training, leaving that narrow research carve-out unchanged while commercial text and data mining continues to require a licence.

    Text and data mining (TDM) is the automated analytical process of extracting patterns, structured data, and statistical relationships from digital text, images, and other content — typically the first stage in assembling a corpus to train a machine-learning or generative AI model.

    What is the UK’s text and data mining copyright exception?

    Section 29A of the Copyright, Designs and Patents Act 1988 allows a person with lawful access to a copyright work — for example through a subscription, a library licence, or open web access — to make a copy of that work for the purpose of computational analysis, provided the resulting copy is used solely for non-commercial research. The exception was introduced in 2014, making the UK one of the earliest jurisdictions to legislate specifically for TDM.

    Two features make Section 29A unusually workable for universities. First, it extends to individual researchers, not only to the institutions that employ them. Second, under section 29A(5), any contract term that purports to prevent or restrict this lawful copying is unenforceable — a publisher cannot use its licence terms to override the statutory right. What the exception does not do is authorise commercial use: a university spin-out or an industry-funded lab training a model for eventual commercial deployment sits outside its protection.

    What broader exception did the government propose?

    The UK Intellectual Property Office first floated a much wider TDM exception in 2022, permitting data mining for any purpose, including commercial AI training, with no opt-out for rights holders. That proposal was abandoned in 2023 after sustained opposition from publishers, musicians, and other creative-industry rights holders, who argued it would let AI developers use copyrighted work without consent or payment.

    The government returned to the question in its December 2024 consultation, Copyright and Artificial Intelligence, which ran for ten weeks, from 17 December 2024 to 25 February 2025. This time the model differed: a rights-reservation (“opt-out”) mechanism paired with a broad exception covering unreserved material, alongside new transparency obligations requiring AI developers to disclose what content they use and how they acquire it. The design echoed Article 4 of the EU’s Digital Single Market (DSM) Directive, and the consultation set out three broad directions: strengthen licensing, introduce the opt-out exception, or make no legislative change.

    • Option A — status quo: retain Section 29A unchanged, relying on licensing markets to develop organically.
    • Option B — broad exception with opt-out: allow TDM for any purpose unless a rights holder actively reserves their rights.
    • Option C — licensing-led framework: mandate transparency and collective licensing infrastructure without a new statutory exception.

    What did the UK government decide in March 2026?

    The government confirmed in March 2026 that it will not proceed with a new text and data mining exception. According to The Ivors Academy, which represents songwriters and composers and was among the respondent organisations, 88% of consultation respondents called for stronger copyright protection and licensing rather than a broadened exception. Section 29A therefore remains the operative law: non-commercial research TDM is lawful without a licence, and everything outside that narrow purpose still requires rights-holder permission.

    Rather than legislating a new exception, the government is directing policy into four linked work programmes: digital replicas (deepfake-style AI recreations of a person’s voice or likeness), AI-output labelling, creator control and transparency obligations for AI developers, and support for independent creatives. Legislation on transparency — requiring AI developers to disclose training data provenance — remains under active consideration even though the exception itself has been shelved.

    How does the UK exception compare with the EU’s TDM rules?

    The UK operates a single, narrower exception than the EU, which — under the 2019 DSM Directive — runs two parallel TDM exceptions with different scopes and different rules on opting out.

    Feature UK — Section 29A, CDPA 1988 EU — Article 3, DSM Directive EU — Article 4, DSM Directive
    Permitted purpose Non-commercial research only Scientific research Any purpose, including commercial
    Eligible parties Research institutions and individual researchers Research organisations and cultural heritage institutions Any lawful user
    Opt-out for rights holders None — contract terms restricting it are unenforceable None Yes — rights holders may reserve rights via machine-readable means
    Extends to databases No — copyright works only Yes Yes
    Commercial research covered No Limited, in some readings Yes

    The UK’s December 2024 proposal effectively asked whether the country should import something resembling Article 4 — a broad, opt-out-based exception. Following the March 2026 decision, the UK still has no equivalent, leaving a materially narrower legal basis for commercial AI training than exists across the EU.

    What does this mean for research libraries and AI labs?

    For university libraries and text-mining labs conducting genuinely non-commercial research, the practical position is unchanged: Section 29A continues to authorise corpus-building from lawfully accessed material, and publisher licence terms cannot override that right. Institutions should still document lawful access and non-commercial purpose, since the boundary — not the existence — of the exception is what gets tested.

    For AI developers, commercial spin-outs, and industry-funded research partnerships, the position stays materially harder than under a broad opt-out exception. These organisations must continue to:

    • Secure licences from publishers, image libraries, and other rights holders before using material for training corpora with any commercial application.
    • Track the government’s forthcoming transparency obligations, which may require disclosure of training-data provenance even without a new exception.
    • Watch the EU comparison closely — jurisdictions with broader TDM rights may become more attractive for model training, a concern the government itself raised in 2024.
    • Distinguish clearly between non-commercial research activity (protected) and downstream commercial application of the same corpus (not protected).

    Research administrators managing institutional research administration functions will need to keep licensing and TDM-exception boundaries visible in data-management and AI-use policies, particularly where university-industry collaborations blur the line Section 29A treats as decisive.

    Frequently asked questions

    What is the text and data mining exception in UK copyright law?

    The text and data mining exception is a provision in Section 29A of the Copyright, Designs and Patents Act 1988 that allows lawful users to copy copyright works for computational analysis, but only for non-commercial research. It does not cover commercial AI training, and any contract term restricting this lawful use is unenforceable under section 29A(5).

    Does the UK allow AI companies to train models on copyrighted text without a licence?

    No. Outside the narrow non-commercial research exception, UK copyright law requires AI developers to obtain a licence from rights holders before using protected text, images, or data for training. The government confirmed in March 2026 it will not introduce a broader exception, so commercial text and data mining still needs permission.

    What was the UK government’s opt-out proposal for AI and copyright?

    In its December 2024 consultation, the government proposed letting rights holders reserve their rights (opt out) while introducing a wide exception permitting AI developers to mine unreserved material at scale — modelled loosely on the EU’s Article 4 DSM Directive exception. This proposal was not taken forward.

    How is the UK’s TDM exception different from the EU’s?

    The UK’s single exception (Section 29A) covers only non-commercial research but extends to individual researchers, not just institutions. The EU’s DSM Directive instead runs two exceptions: Article 3 for research organisations and cultural-heritage bodies, and Article 4, a broader opt-out exception the UK ultimately declined to replicate.

    Looking ahead

    The March 2026 decision closes one chapter of the UK’s AI-copyright debate but opens another: a licensing-led, transparency-driven framework built around four active work programmes rather than a single statutory fix. For research libraries, the immediate legal position is stable. For AI labs and commercial partnerships built on UK-hosted training data, the absence of a broad exception means licensing negotiations — not statute — will continue to determine what can lawfully be mined.

  • China AI Regulation for Research Collaboration

    China’s AI regulation centres on the Interim Measures for the Management of Generative Artificial Intelligence Services (effective 15 August 2023), which require AI-service providers to disclose AI use and forbid listing generative AI as a co-author. For Western universities collaborating with Chinese institutions, the rules affect authorship credit, cross-border data transfer, and how AI tools may be used in co-supervised research.

    China’s Interim Measures for the Management of Generative Artificial Intelligence Services is the country’s first binding, AI-specific regulation, jointly issued by the Cyberspace Administration of China (CAC) and six other ministries. It sits alongside the Cybersecurity Law, the Data Security Law and the Personal Information Protection Law (PIPL) as the legal backbone for how AI-enabled research involving Chinese partners must be conducted.

    This matters for research administrators well beyond China’s borders. Joint-authorship agreements, data-sharing memoranda and co-supervision arrangements with Chinese universities now have to reconcile Chinese disclosure and labelling duties with the authorship norms already in force under COPE, ICMJE and journal policy in the EU, UK and US.

    What China’s Interim Measures for Generative AI actually require

    The Interim Measures require providers of public-facing generative AI services to register with the CAC, prevent outputs that undermine state security or social stability, and take measures against algorithmic bias. Internal research and development that is not offered as a public-facing service is treated more lightly, but outputs intended for publication or public dissemination fall squarely within scope.

    Two further instruments extend the regime. The Measures for Labeling AI-Generated and Synthesized Content, paired with the national standard GB 45438-2025, took effect in September 2025 and require visible or embedded labels on AI-generated text, images and audio distributed in China. The Ministry of Science and Technology’s guidelines on responsible research conduct, issued in December 2023, apply specifically to academic work: they prohibit using generative AI to draft funding applications and require researchers to disclose any generative AI use in their methodology.

    China has not enacted a single, comprehensive AI statute. A draft Artificial Intelligence Law has appeared on the National People’s Congress Standing Committee’s legislative agenda since 2023, but no official draft had been released as of December 2025, and the enactment timeline remains unclear.

    How China’s framework compares with the EU, UK and US

    None of the four major jurisdictions regulates AI in research collaboration through a single dedicated instrument. Each layers AI-specific rules on top of existing data-protection, cybersecurity and research-integrity frameworks, but the point at which those rules bind differs sharply.

    Jurisdiction Core AI instrument Status (as of mid-2026) Authorship / disclosure rule for research
    China Interim Measures for Generative AI Services (2023) plus labelling rules (2025) In force; comprehensive AI Law still in draft Ministry of Science and Technology guidelines bar listing AI as a co-author; AI use must be disclosed
    European Union AI Act, Regulation (EU) 2024/1689 General-purpose AI obligations apply from August 2025; most other obligations from August 2026 No AI-authorship bar in the Act itself; publishers apply COPE and ICMJE norms
    United Kingdom No dedicated AI statute; pro-innovation, regulator-led approach Existing regulators (ICO and sector bodies) apply cross-cutting principles COPE- and ICMJE-aligned: AI cannot be listed as author; disclosure expected in methods sections
    United States No comprehensive federal law; state statutes (e.g. the Colorado AI Act) and the voluntary NIST AI Risk Management Framework Patchwork of state laws; federal approach still executive-order-driven NIH bars AI from being listed as an author or used by peer reviewers to evaluate applications; journals follow ICMJE/COPE

    The practical convergence is striking: China, the EU, the UK and the US all reach the same conclusion on authorship — a generative AI system cannot satisfy the accountability that authorship implies — even though none of them arrives there through identical legislation.

    What this means for joint authorship and contributor disclosure

    China’s Ministry of Science and Technology guidelines and the international consensus reflected in ICMJE recommendations and COPE position statements agree on one point: generative AI tools cannot be listed as authors or contributors, because they cannot take responsibility for the accuracy and integrity of the work. This aligns with the accountability criterion embedded in the CRediT contributor role taxonomy, which CASRAI originated in 2014 and which is now stewarded by NISO as ANSI/NISO Z39.104-2022.

    For joint publications with Chinese co-authors, this means AI-assistance disclosure statements now need to satisfy two regimes at once: China’s requirement to label AI-generated content and disclose AI use in the methodology, and the contributor-role documentation expected by journals following CRediT or ICMJE authorship criteria. A single disclosure paragraph, drafted to meet the stricter of the two standards, is usually sufficient — but it should name the specific generative AI tool, its role, and confirm that no tool is credited as an author or contributor.

    • Confirm which named human contributors meet Chinese and Western authorship criteria before drafting the manuscript.
    • Record AI-tool use (what, where, why) in a disclosure statement that satisfies both the Chinese labelling requirement and journal policy.
    • Never list a generative AI system as an author, co-author or contributor under any of the four frameworks compared above.

    Data-sharing and cross-border transfer requirements

    Research data moving out of China is governed by the Data Security Law and the Personal Information Protection Law, not by the Interim Measures themselves. Transfers of “important data” or bulk personal information generally require a CAC security assessment, a process legal trackers monitoring Chinese compliance report can take several months to clear. Projects that involve Chinese human genetic resources — common in biomedical and health-informatics collaborations — additionally require prior approval from the Ministry of Science and Technology before data can be shared internationally.

    Co-supervised doctoral projects that route data through a public-facing generative AI service add a further layer: the service falls within the Interim Measures’ registration and labelling scope, even where the underlying collaboration is privately arranged between two universities.

    Common questions on China’s AI regulation and research collaboration

    Does China have a comprehensive AI law?

    No. As of mid-2026, China has no single, comprehensive AI statute; regulation proceeds through targeted instruments — the Cybersecurity Law, the Data Security Law, the Personal Information Protection Law, and AI-specific measures such as the Interim Measures for Generative AI. A draft national Artificial Intelligence Law remains under review, with no confirmed enactment timeline.

    What is the Interim Measures for the Management of Generative AI Services?

    It is China’s first binding national regulation aimed specifically at generative AI, effective 15 August 2023. Issued jointly by the Cyberspace Administration of China and six ministries, it requires providers to register services, label AI-generated content, and prevent outputs that undermine state security or social stability.

    Can AI be listed as a co-author on Chinese-affiliated research?

    No. China’s Ministry of Science and Technology guidelines on responsible research conduct, issued in 2023, prohibit listing generative AI tools as co-authors and require disclosure of AI use in manuscripts and funding applications. This mirrors COPE and ICMJE guidance already applied by EU, UK and US publishers.

    Do foreign researchers need approval to share data with Chinese AI research partners?

    Often, yes. Under the Data Security Law and PIPL, transferring research data — especially human genetic or health data — outside China can require a Cyberspace Administration of China security assessment. Projects involving Chinese human genetic resources additionally need Ministry of Science and Technology approval before international sharing proceeds.

    Implications for research offices

    Research offices managing joint-authorship agreements, data-sharing memoranda or co-supervision arrangements with Chinese institutions need compliance processes that satisfy Chinese disclosure and security-review requirements without weakening the authorship and contributor-role standards already expected by Western journals and funders. Treating China’s rules as an additional layer on top of existing CRediT-based authorship practice, rather than a separate compliance track, keeps the paperwork proportionate.

    China’s regulatory posture is still moving: the Ministry of Science and Technology, the CAC and the State Council have all issued new instruments since mid-2025. Institutions with active China partnerships should treat authorship-disclosure and data-transfer procedures as living documents, reviewed annually against the current Chinese, EU, UK and US rules.

  • Sovereign AI Fund: The University Research Route

    The UK’s Sovereign AI Fund is a £500 million state-backed venture capital vehicle, launched by the Department for Science, Innovation and Technology (DSIT) in April 2026, that makes equity investments and compute grants in British AI startups — it is not a university research grant scheme. University research groups instead access AI compute through the separate AI Research Resource (AIRR) open-access calls and funding through UK Research and Innovation (UKRI), routes this article sets out in detail.

    The sovereign ai fund operates like a professional venture capital firm with the balance sheet of the state behind it. Understanding where its remit stops — and where academic infrastructure routes begin — matters for any institution tracking funder and national-infrastructure policy in 2026.

    Contents

    What is the UK’s Sovereign AI Fund?

    The Sovereign AI Fund is a £500 million venture capital fund established by the UK government in April 2026 to invest directly in early-stage and growth-stage British AI companies. It sits within DSIT’s Sovereign AI Unit and was announced by Technology Secretary Liz Kendall and Chancellor Rachel Reeves as part of the government’s wider “AI maker, not AI taker” strategy first set out in the AI Opportunities Action Plan of January 2025.

    Equity cheques typically run from £1 million to £10 million, with the Fund’s own published materials citing up to £20 million for later-stage follow-on rounds. Portfolio companies also receive fully funded access to UK supercomputers — up to 1 million GPU hours per startup — plus fast-tracked visa decisions and help navigating procurement and regulation. The Fund is chaired by James Wise of Balderton Capital, with Suzanne Ashman appointed Managing Partner of its investment committee in May 2026.

    How do the Fund’s capital and compute tracks differ?

    The Sovereign AI Fund runs two distinct tracks, and conflating them is the most common misreading of the programme. The first is direct equity investment; the second is compute-only access to the AI Research Resource (AIRR) supercomputer network, awarded competitively without an immediate equity stake.

    By May 2026, three companies had received direct equity backing: Callosum (an AI infrastructure orchestration startup founded by Cambridge PhDs, and the Fund’s first investment), Ineffable Intelligence (founded by David Silver, former Head of Reinforcement Learning at Google DeepMind), and Isomorphic Labs (the drug-discovery company founded by Demis Hassabis). A further six companies — Cosine, Doubleword, Odyssey, Prima Mente, Twig Bio and Cursive — received AIRR compute allocations only, with the Fund holding a right of first refusal on future equity investment in several of them.

    • Equity track: capital plus compute plus visas, in exchange for a stake in the company.
    • Compute-only track: AIRR GPU allocation via a competitive open call, assessed on strategic relevance, technical quality and material compute need, with no immediate equity taken.
    • Strategic Assets Grants Programme: a separate £282 million pot funding shared datasets and infrastructure “critical inputs” for the wider AI ecosystem.

    Can university research groups access the Sovereign AI Fund directly?

    No. The Sovereign AI Fund is structured as a commercial venture-investment vehicle for UK-registered companies, not a research council grant scheme, and university departments are not eligible applicants in their own right. Academic groups seeking large-scale AI compute or project funding should instead route through the AI Research Resource and UKRI — mechanisms built for exactly this purpose and administered separately from the Fund.

    The AIRR network — which includes Isambard-AI at the University of Bristol and Dawn at the University of Cambridge — runs its own “AI Open Access” calls for academic-led projects requiring substantial GPU capacity in priority areas such as materials science, medical research and engineering biology. Eligibility generally requires the project lead to hold a lecturer-level (or equivalent) post at an organisation eligible for UKRI funding. Direct funding for AI-related research, meanwhile, flows through UKRI and its constituent councils, including the Engineering and Physical Sciences Research Council (EPSRC); UKRI has stated a £1.6 billion AI investment commitment across 2026–2030, and new AI research labs led by Oxford and UCL are set to receive up to £60 million in government funding.

    The overlap is real but indirect. Several portfolio companies have active university collaborations — Prima Mente works with Oxford, Imperial and Edinburgh on biological foundation models, and Callosum’s founders are Cambridge PhDs — but these run through standard knowledge-transfer channels, not Fund eligibility itself.

    Sovereign AI Fund vs AIRR vs UKRI: how the three routes compare

    Research administrators fielding questions from principal investigators or technology-transfer offices need a quick way to route enquiries correctly. The table below sets out the three mechanisms side by side.

    Mechanism Who it is for What it provides Cost to recipient
    Sovereign AI Fund (equity track) UK-registered AI startups £1m–£20m capital, up to 1m GPU hours, fast-track visas Equity stake taken by the state
    Sovereign AI Fund (compute-only track) Selected AI startups (competitive call) AIRR GPU allocation, no immediate capital None initially; right of first refusal on future investment
    AIRR AI Open Access University-led research teams (lecturer-level PI+) GPU time on Isambard-AI, Dawn and other AIRR nodes None — competitive academic allocation
    UKRI / EPSRC grants Eligible UK research organisations Project and infrastructure funding None — grant funding, no equity

    What does this mean for research administrators and institutional leaders?

    Institutions should treat the Sovereign AI Fund and AIRR/UKRI as two parallel but interlocking systems rather than one policy. Grants offices and research administrators should not point commercial spin-outs toward UKRI grant calls, nor point academic groups toward the Fund’s equity application form — the eligibility gates and outcomes differ fundamentally.

    There is also a capacity-planning implication. AIRR nodes such as Isambard-AI and Dawn now serve both academic open-access calls and Sovereign AI Fund-badged startup allocations from the same national compute pool. As the Fund plans to allocate compute “worth tens of millions of pounds” to startups this year, institutions relying on AIRR for research-council-funded work should factor potential contention into project timelines.

    Spin-out pathways deserve attention too. Academic teams that build a proof of concept using AIRR or UKRI-funded compute may later seek Sovereign AI Fund equity once they incorporate as a company — a legitimate sequence, but one that requires institutions to manage IP and data-rights handover clearly between the academic and commercial phases.

    Common questions about the Sovereign AI Fund

    What is a sovereign AI fund?

    A sovereign AI fund is a state-backed investment vehicle that deploys public capital, compute and strategic support into domestic AI companies. In the UK, this is the £500 million Sovereign AI Fund, which operates like a venture capital firm but is run by DSIT’s Sovereign AI Unit rather than a private investor.

    What exactly is sovereign AI?

    Sovereign AI refers broadly to AI capability — models, chips, data and infrastructure — that is built, controlled and hosted within a nation’s own jurisdiction rather than rented from foreign providers. The UK’s use of the term ties directly to the AI Opportunities Action Plan’s “AI maker, not AI taker” framing, adopted to reduce dependence on overseas AI infrastructure.

    Is Sovereign AI free to use for universities?

    The Sovereign AI Fund itself is not “free” — its equity track exchanges capital and compute for a stake in the company. For universities, the relevant comparison is AIRR’s Open Access compute calls and UKRI grant funding, both of which award GPU time or research funding without taking equity or ownership.

    What’s next for sovereign AI compute access?

    The Fund has confirmed it will keep assessing applications on a rolling basis and was, at its first cohort announcement, in discussions with around 30 further firms over AIRR access. The signal to watch is whether DSIT and UKRI publish a shared capacity-planning framework for AIRR, since academic and Fund-backed commercial demand now draw on the same national compute pool. Institutions that map their AI research pipeline against all three routes now, rather than after a bottleneck emerges, will be better placed as the 2026–2030 funding period unfolds.

    Institutions building AI-adjacent research programmes should track how funder infrastructure policy intersects with broader research administration practice, since compute-access rules now shape project feasibility directly.

  • AI Opportunities Action Plan: Research, Year One

    The AI Opportunities Action Plan, published by the UK Department for Science, Innovation and Technology (DSIT) on 13 January 2025, has met 38 of its 50 actions one year on, according to the government’s own “One Year On” progress report published 29 January 2026. For university research, delivery is real but uneven: new supercomputing capacity has landed, while AI Growth Zones and the Sovereign AI Unit’s research-facing funding remain mostly in the “designated but not yet delivered” phase.

    The AI Opportunities Action Plan is a 50-recommendation UK government strategy, authored by entrepreneur Matt Clifford, that commits the state to expanding compute infrastructure, unlocking public data assets, developing AI talent and accelerating public- and private-sector AI adoption. The government accepted all 50 recommendations in its January 2025 response and pledged a Compute Strategy for Spring 2025.

    Contents

    What compute has been delivered for university research?

    Compute is the section of the Action Plan with the clearest research-facing delivery record. The government committed £2 billion to expand UK public compute capacity twentyfold by 2030, and the first tranche has already reached campus-hosted infrastructure rather than staying at the announcement stage.

    • Isambard-AI, the flagship AI Research Resource (AIRR) supercomputer, launched at the University of Bristol in July 2025.
    • The DAWN supercomputer at the University of Cambridge was confirmed in January 2026 to receive a sixfold capacity increase, targeted for completion by Spring 2026.
    • A new national supercomputer backed by £750 million will be hosted in Scotland, coupled to the International Data Facility at the Edinburgh Parallel Computing Centre so researchers can run models against large datasets in a secure environment.
    • Up to £250 million has been earmarked specifically to scale cloud capacity within the AI Research Resource, the free-at-point-of-use compute pool for UK researchers, businesses and start-ups.

    This is the plan’s strongest evidence base: named machines, named universities and confirmed dates, rather than funding envelopes still awaiting allocation.

    Are AI Growth Zones and the Sovereign AI Fund reaching universities?

    Two of the plan’s highest-profile mechanisms — AI Growth Zones and the Sovereign AI Unit — show a wider gap between announcement and research-facing delivery than the compute programme does.

    Five AI Growth Zones have been designated across Great Britain, including two in Wales and one in Scotland, which the government reports have generated £28.2 billion in investment and more than 15,000 jobs, alongside £5 million of targeted local funding per zone. A new AI Growth Zone Delivery Unit has been created to broker power, planning and offtake agreements. But the government’s own document frames the coming year’s priority as “bringing AI Growth Zones from designation to delivery” — an explicit admission that build-out, not designation, is the unfinished task, and universities inside these zones are not yet reporting operational access to zone-linked infrastructure.

    The Sovereign AI Unit, backed by up to £500 million, has made a small number of research-adjacent commitments in its first year: it allocated sovereign compute to the University of Cambridge’s MACE materials-discovery foundation model, and provided £8 million in seed funding to the OpenBind consortium’s structural dataset for AI-driven drug discovery. The unit’s main investment phase — chaired by James Wise of Balderton Capital — does not launch until April 2026, meaning the bulk of its £500 million has not yet been deployed to UK AI companies or research spin-outs.

    Mechanism Committed funding Research-facing status, January 2026
    AI Research Resource / Isambard-AI, DAWN £2bn (20x compute by 2030), £250m cloud capacity Delivered — operational at Bristol, Cambridge scaling by Spring 2026
    Scotland national supercomputer + EPCC data facility £750m Committed, under construction
    AI Growth Zones (5 designated) £28.2bn investment reported, £5m per zone Designated; delivery unit only just established
    Sovereign AI Unit Up to £500m Early pilot investments only; main phase from April 2026
    Health Data Research Service Up to £600m (government + Wellcome) Leadership appointed Jan 2026; not yet operational

    What hasn’t been delivered yet?

    Twelve of the plan’s 50 actions remain unmet at the one-year mark. For research administrators, the most consequential gaps are structural rather than financial:

    • The AI Growth Lab cross-economy regulatory sandbox — intended to let promising AI applications, including research tools, trial in real-world settings ahead of full regulation — is still at the call-for-evidence stage, not operational.
    • The Health Data Research Service, jointly backed by government and the Wellcome Trust with up to £600 million, appointed its CEO (Dr Melanie Ivarsson) and Chair (Baroness Nicola Blackwood) only in late 2025 and January 2026 respectively; the single secure access point to national health datasets it promises is not yet live for researchers.
    • National Data Library funding of over £100 million has produced guidance and an open call for data proposals, but not yet a working data-sharing infrastructure that institutions can plug into.

    These are the items where the difference between “committed” and “delivered” matters most for institutions planning multi-year research infrastructure roadmaps.

    Answer-first: common questions on the Action Plan

    What is the UK AI investment plan?

    The UK’s core AI investment framework is the AI Opportunities Action Plan, backed by roughly £2 billion for compute expansion, a £500 million Sovereign AI Unit, and further sector funding through the 2025 Industrial Strategy and Spending Review 2025 settlements for AISI and the National Data Library.

    How much is the UK government investing in AI?

    Across the Action Plan’s first year, headline commitments include £2 billion for 20x compute capacity by 2030, £750 million for a new Scotland-based national supercomputer, up to £500 million for the Sovereign AI Unit, and £240 million for the AI Security Institute, alongside £600 million jointly with Wellcome for health data infrastructure.

    What are AI Growth Zones and do universities benefit?

    AI Growth Zones are five government-designated regions with streamlined planning and energy access to accelerate data-centre build-out. Universities within or near these zones have not yet reported operational research access, as the government itself states delivery — not designation — is the unfinished 2026 priority.

    What is the UK Sovereign AI Fund?

    The Sovereign AI Unit is a government-backed fund of up to £500 million designed to invest in and support UK AI companies across critical parts of the AI value chain. Its main investment phase, chaired by James Wise of Balderton Capital, begins in April 2026, after a first year of limited pilot allocations.

    What this means for research administrators

    Institutions should treat the Action Plan’s compute strand as substantially delivered and plan around it: AIRR access, Isambard-AI and the Cambridge DAWN expansion are real, usable capacity for 2026 research bids. AI Growth Zone and Sovereign AI Unit funding, by contrast, should still be treated as pipeline rather than available resource — research offices tracking institutional eligibility for zone-linked infrastructure or sovereign-fund co-investment should expect further delivery milestones through 2026 rather than immediate access. The Health Data Research Service is worth monitoring closely by any institution with health-data-dependent research programmes, given the scale of the £600 million commitment relative to its current pre-operational status.

    Outlook: the next year of delivery

    With 38 of 50 actions met, the government has moved the Action Plan from strategy document to partially built infrastructure. The test for its second year is converting designation into delivery — turning AI Growth Zones into working data-centre capacity, and the Sovereign AI Unit’s £500 million into deployed investment — while bringing the Health Data Research Service and National Data Library from governance milestones to infrastructure researchers can actually use. For university research administration teams, that distinction between committed and delivered funding will determine what can realistically be built into 2026–27 grant and infrastructure planning.

  • AI Security Institute UK: What the Rebrand Means

    The UK AI Security Institute (AISI) is the government’s frontier-AI testing body, renamed in February 2025 from the AI Safety Institute to signal a sharper focus on cyber-harms, national security and misuse risk rather than broader ethical questions such as bias. For universities, the practical mandate — pre-deployment model access, evaluation infrastructure, and grant funding via the Alignment Project — has not shrunk, but proposals now compete more strongly when framed around security-relevant risk.

    The AI Security Institute is a directorate of the UK’s Department for Science, Innovation and Technology (DSIT) whose mission, in its own words, is “to equip governments with a scientific understanding of the risks posed by advanced AI.” It sits inside government but is designed, in AISI’s own framing, “like a startup in the government.”

    What is the AI Security Institute, and how did it start?

    AISI traces its origins to the Frontier AI Taskforce, launched with an initial £100 million budget in April 2023. It was formally established as the AI Safety Institute at the AI Safety Summit held at Bletchley Park in November 2023 — the world’s first major intergovernmental gathering on frontier-AI risk. The institute now operates on £66 million of funding per financial year, plus long-term resourcing commitments from DSIT.

    Its core activities are unchanged by the rename: testing leading AI systems before and after public release, informing UK and allied policymakers on emerging capabilities, and running an open-source evaluation platform called Inspect that lets companies, governments and academics run standardised safety tests. AISI holds pre-deployment access agreements with Anthropic, Google DeepMind and OpenAI, giving it — and by extension its research partners — visibility into frontier models before the public sees them.

    Why was the AI Safety Institute renamed the AI Security Institute?

    The rename took effect in February 2025, reported first by Infosecurity Magazine on 14 February that year. Observers, including Wikipedia’s contributor consensus on the institute’s own entry, read the change as signalling that AISI would step back from broader ethical territory — algorithmic bias, freedom of speech in AI systems — and concentrate on the most severe, security-relevant harms: cyberattacks, biological and chemical weapons uplift, and loss of control over autonomous systems.

    The shift echoed a parallel move in Washington. In June 2025, the US AI Safety Institute was renamed the Center for AI Standards and Innovation (CAISI), with then-Commerce Secretary Howard Lutnick stating that AI evaluation should not be used “under the guise” of restricting innovation. The UK’s own rename predates that, but both reflect a broader 2025 pivot among Western AI-safety bodies away from precautionary, existential-risk framing and toward concrete national-security and economic-competitiveness mandates.

    AISI’s published research areas now read as a security taxonomy rather than a general safety agenda: Cyber Misuse, Safeguards, Alignment, Control, Autonomy, Human Influence and Societal Resilience. Each maps to a specific threat model government departments can act on, rather than an open-ended ethics brief.

    How does AISI fit into the International Network of AI Safety Institutes?

    The International Network of AI Safety Institutes was agreed at the AI Seoul Summit in May 2024 and held its first formal meeting in November 2024. Its founding members are the UK, the United States, the European Union, Japan, France, Singapore, South Korea, Canada, Kenya and Australia (Australia’s own AI Safety Institute was announced in November 2025, after the network’s launch). Kenya remains the only African member.

    Membership matters for universities in a practical sense: the network’s joint testing exercises — including a July 2025 evaluation exercise on AI-agent risks such as sensitive-data leakage — set shared technical standards that AISI then applies domestically. A university research group that aligns its evaluation methodology with AISI’s is, by extension, aligning with a standard that a further nine jurisdictions recognise.

    International Network of AI Safety Institutes — selected member bodies
    Jurisdiction Institute Established
    United Kingdom AI Security Institute (AISI) Nov 2023; renamed Feb 2025
    United States Center for AI Standards and Innovation (CAISI) Nov 2023; renamed Jun 2025
    European Union EU AI Office May 2024
    France INESIA Jan 2025
    Japan J-AISI Feb 2024
    Singapore Digital Trust Centre (AISI-designated) Renamed May 2024
    Canada Canadian AI Safety Institute Nov 2024

    What does the rebrand mean for university model-access and red-teaming partnerships?

    For institutions pursuing model-access agreements or red-teaming collaborations, the security framing changes what gets funded, not whether funding exists. AISI mobilises more than £15 million in grants through the Alignment Project, open to university and non-profit researchers globally, and its priority-access arrangement covers over £1.5 billion of compute through the UK’s AI Research Resource and exascale supercomputing programme — a resource pool researchers can draw on for evaluation-relevant work.

    Three practical shifts follow from the rebrand:

    • Proposal framing: research questions pitched around cyber-misuse, safeguard robustness or loss-of-control scenarios now map more directly onto AISI’s stated research areas than proposals framed around general-purpose ethics or bias auditing.
    • Compute and model access: AISI’s pre-deployment agreements with frontier labs give it privileged visibility that university partners can sometimes access via joint evaluation projects — but access is gated by relevance to AISI’s security-risk taxonomy.
    • Policy context: the UK’s AI Opportunities Action Plan, published 13 January 2025, commits to expanding sovereign AI compute capacity at least 20-fold by 2030 and created a Sovereign AI Unit with up to £500 million in funding — infrastructure that sits alongside, not inside, AISI’s own compute allocation, but which shapes the wider funding climate university research offices are now navigating.

    Research administrators should note that AISI’s grant and access programmes are administered separately from Research England and UKRI mainstream funding lines, so due-diligence and reporting requirements differ from a standard research-council award.

    Answer-first Q&A

    Did the UK change the name of the AI Security Institute?

    Yes. The UK’s AI Safety Institute was renamed the AI Security Institute in February 2025. The institute itself did not change its legal status or parent department — it remains a directorate of DSIT — but its public mission language and research priorities shifted toward cyber-harms and national-security risk.

    What exactly does “AI security” mean in this context?

    In AISI’s usage, AI security covers risks where advanced models are misused for cyberattacks, biological or chemical weapons development, or where systems act autonomously beyond human oversight. It is narrower than the earlier “AI safety” framing, which also covered algorithmic bias and broader societal harms.

    Who leads the AI Security Institute?

    Adam Beaumont, formerly GCHQ’s Chief AI Officer, is Interim Director. Jade Leung, the Prime Minister’s AI Advisor and a former OpenAI governance lead, serves as Chief Technology Officer. Ian Hogarth chairs the institute, and its advisory board includes AI researcher Yoshua Bengio.

    Who funds the AI Security Institute?

    AISI is funded directly by the UK government through DSIT, at £66 million per financial year, with long-term resourcing commitments. It separately mobilises over £15 million in external grant funding through the Alignment Project for researchers, including those at universities, working outside government.

    Implications for research administrators

    The safety-to-security rebrand is best read as a narrowing of mandate language, not a withdrawal from academic engagement. Universities seeking model-access or red-teaming relationships with AISI should expect proposals to be evaluated more explicitly against its published risk taxonomy — cyber misuse, safeguards, alignment, control, autonomy, human influence and societal resilience — than against a general AI-ethics brief.

    Institutions should also track the International Network of AI Safety Institutes’ joint testing exercises as a source of emerging shared methodology, since AISI’s domestic evaluation standards are increasingly set in coordination with nine other jurisdictions rather than unilaterally. As the UK’s sovereign compute build-out under the AI Opportunities Action Plan proceeds toward its 2030 target, research offices with evaluation, red-teaming or alignment capacity are positioned to benefit from both AISI’s own grant lines and the wider national compute expansion.

    CASRAI tracks research-administration implications of national AI-governance bodies as part of its broader coverage of the standards landscape; see the CASRAI Dictionary for related terminology and the research administration hub for adjacent policy explainers.

  • UK Association to Horizon Europe: 2026 Rules for Grant Administrators

    UK association to Horizon Europe is the status, formalised on 4 December 2023 and effective from 1 January 2024, under which UK universities, businesses and public research bodies participate in the EU’s €95.5 billion programme on equal terms with EU member states — funded directly by the European Commission rather than through the UK’s earlier domestic guarantee.

    Horizon Europe association is a treaty-level arrangement, agreed under the UK-EU Trade and Cooperation Agreement, that gives a non-EU country’s researchers the same eligibility, funding rates and consortium-leadership rights as an EU member state, in exchange for a calculated financial contribution and an EU-favoured correction mechanism.

    What does UK “associated country” status mean in practice?

    Associated country status means UK entities are treated as if they were based in an EU member state for the purposes of Horizon Europe eligibility. UK organisations can lead consortia, count towards the minimum-country thresholds required for transnational calls, and receive grant payments directly from the European Commission for Work Programme 2024 onward.

    This is a material change from the 2021-2023 period, when UK applicants could be evaluated by the EU but could not lead consortia or count towards minimum-country rules — a gap that pushed many UK institutions into supporting rather than coordinating roles.

    How is the Horizon Europe guarantee scheme winding down?

    The UK government’s Horizon Europe guarantee — a domestic UK Research and Innovation (UKRI) scheme that paid successful UK applicants directly when EU payment channels were unavailable during the association gap — now applies only to grants awarded under Work Programmes 2021, 2022 and 2023. It does not cover Work Programme 2024 or later calls, which are funded by the European Commission itself.

    UKRI reported that the guarantee had awarded more than £1 billion by April 2023, rising to over £2 billion across more than 4,000 verified grants by September 2024. The scheme remains open to close out legacy 2023 Work Programme calls but is not being extended to new competitions — grant offices should treat it as a closing legacy channel, not an ongoing funding route.

    Feature Legacy guarantee (WP2021-2023) Association (WP2024-2027)
    Funding source UK government, via UKRI European Commission, direct
    Administered by UKRI Horizon Europe guarantee team European Commission / Funding & Tenders Portal
    Consortium leadership Not permitted Permitted
    Counts to minimum-country threshold No Yes
    Status in 2026 Closing out legacy calls only Standard, ongoing route

    Which application route applies to your grant?

    Every Horizon Europe call carries a call identification number that states its Work Programme year. Grant administrators should check this ID before advising a principal investigator on eligibility or funding source, because the two routes carry different obligations.

    • If the call ID references 2021, 2022 or 2023, it falls under the legacy UK guarantee: apply directly to the EU as a beneficiary, and — if successful — receive funding from UKRI rather than Brussels.
    • If the call ID references 2024, 2025, 2026 or 2027, it falls under UK association: the organisation applies, is evaluated and is paid exactly as an EU member-state entity would be, via the Funding & Tenders Portal.
    • Before submitting, confirm the organisation holds a valid Participant Identification Code (PIC) on the Funding & Tenders Portal — this is required regardless of which route applies.
    • Most collaborative calls require a minimum of three legal entities established in three different EU member states or associated countries; UK entities now count towards that minimum under association.

    What is the UK-EU correction mechanism?

    Association is not simply “join and pay a flat fee.” The UK-EU protocol includes a correction mechanism, described in the House of Commons Library’s briefing on UK participation in EU programmes, that compares what the UK contributes against what UK entities draw down in grants.

    Three thresholds govern it. If UK entities receive more than 8% above the UK’s contribution for two consecutive years, the UK must reimburse the European Commission for the difference. If the UK overpays relative to its drawdown by more than 12%, it may raise the imbalance with the joint Specialised Committee on Participation in Union Programmes. If UK drawdown falls to 16% or less of its contribution in a given year, the UK’s future operational contribution is reduced automatically. This mechanism — not a fixed subscription fee — is what determines the UK’s net cost of association year to year.

    What remains off-limits to UK organisations?

    Association is near-complete but not total. UK entities remain excluded from the European Innovation Council (EIC) Fund, the equity-investment component attached to the EIC Accelerator. UK companies can still apply for EIC Accelerator grant funding and participate in EIC Pathfinder and Transition schemes; only the blended-finance equity strand is closed to them.

    A small number of individual calls also restrict eligibility to EU member states or specific other countries under current Work Programmes; the European Commission has committed to assessing UK access to these on equal terms with other associated countries going forward.

    Answer-first Q&A

    Is the UK associated to Horizon Europe?

    Yes. The United Kingdom has been a fully associated country to Horizon Europe since 1 January 2024, under the UK-EU agreement signed on 4 December 2023. UK universities, SMEs and public-sector research bodies now hold the same funding rights and consortium-leadership rules as EU member-state organisations, with narrow exceptions.

    When did the UK join Horizon Europe?

    The UK and EU reached political agreement on 7 September 2023, signed the finalised text on 4 December 2023, and association became legally effective from 1 January 2024. It applies to all Work Programme 2024 calls onward, including calls that opened before the formal signature date.

    How much does the UK contribute to Horizon Europe?

    The UK pays an annual operational contribution set under the association protocol to the Trade and Cooperation Agreement. A correction mechanism then adjusts this: two consecutive years of UK drawdown exceeding contribution by 8% triggers reimbursement to the EU, while drawdown below 16% of contribution cuts future UK payments automatically.

    Can the UK apply to Horizon Europe?

    Yes. UK organisations can apply to almost every Horizon Europe funding call, lead consortia, and receive grants directly from the European Commission for Work Programme 2024 onward. The main structural exclusion is the European Innovation Council Fund’s equity-investment component under the EIC Accelerator.

    Implications for grant administrators

    Research offices should update internal eligibility guidance to reflect that UK principal investigators can now coordinate Horizon Europe consortia — a role many institutions’ pre-award teams have not resourced for since 2020. Budget templates and financial-reporting workflows built around the UKRI guarantee should be flagged as legacy processes, restricted to residual 2021-2023 awards, and kept separate from Work Programme 2024-2027 grant management, which follows standard EU financial rules and reporting deadlines.

    Institutions should also monitor the correction mechanism’s annual assessment, since a UK reimbursement obligation or a contribution reduction can affect national research-budget planning that indirectly shapes co-funding and matched-funding decisions at institutional level.

    Outlook for 2026 and beyond

    Horizon Europe runs to 2027, with a further multiannual programme under negotiation for the 2028-2034 period. UK association currently covers only the current programme; renewal terms, including whether the correction-mechanism thresholds are renegotiated, are not yet settled. Grant administrators planning multi-year projects that straddle the current and next programming periods should treat continuity of UK association beyond 2027 as unconfirmed rather than assumed, and build contingency language into consortium agreements accordingly.

    For institutions building out research administration capacity around Horizon Europe, the practical priority for 2026 is operational: correctly routing each grant to its Work Programme year, retiring guarantee-era processes, and briefing investigators that UK-led consortia are now the norm, not the exception.

  • UK Clinical Trial Regulations 2026: What Changed on 28 April

    On 28 April 2026, the amended Medicines for Human Use (Clinical Trials) Regulations took full legal effect across England, Wales, Scotland and Northern Ireland. Together with a UK-specific implementation of the international ICH E6(R3) Good Clinical Practice principles, this is the biggest change to clinical trial regulations UK-wide in over two decades. For research offices, sponsors and Research Ethics Committees, the transition period is now over — every application, modification and transparency obligation submitted from this date is assessed against the new framework.

    What changed on 28 April 2026

    The Medicines for Human Use (Clinical Trials) (Amendment) Regulations 2025 were signed into law on 11 April 2025 and, following a 12-month implementation period led jointly by the Medicines and Healthcare products Regulatory Agency (MHRA) and the Health Research Authority (HRA), came into force on 28 April 2026. The Health Research Authority describes it as the largest package of clinical trial regulatory reform in more than 20 years, shaped by a 2022 public consultation with patients, researchers, healthcare professionals and industry.

    Six changes matter most for day-to-day research administration:

    • New terminology. “Amendment” is replaced by “modification”; “subject” becomes “participant”; “trial site” becomes “trial location”; and the role of “authorised health care professional” is removed in favour of a broader health care professional definition for chief investigators and investigators.
    • A codified notification scheme. A new streamlined notification route for the lowest-risk trials and initial applications is now written into law, alongside the existing Combined Review service.
    • UK-specific ICH E6(R3) GCP. All CTIMPs must now adhere to the principles of the latest international Good Clinical Practice guideline, ICH E6(R3), with trials intended to support a marketing authorisation required to comply with the full guideline.
    • A recruitment deadline. Trials are expected to recruit their first UK participant within two years of approval; if recruitment has not started and no extension has been granted, the approval lapses.
    • Simplified consent options. Sponsors of qualifying low-intervention trials may use newly published simplified arrangements for seeking and evidencing informed consent.
    • Alignment for non-CTIMP studies. The HRA has issued parallel changes to how non-CTIMP health and social care research is processed, to keep the wider UK research-governance landscape consistent with the new CTIMP rules.

    Updated model Clinical Trial Agreement (mCTA) forms are also being rolled out to reflect the new definitions and modification categories; research offices negotiating agreements under the old templates should check for the current version before signature.

    Risk-proportionate approvals and modification categories

    The reform’s central aim is proportionality: fewer administrative burdens for low-risk research, without loosening oversight of higher-risk trials. Modifications to an approved trial are now sorted into three statutory categories, each carrying a different regulatory pathway through the MHRA and the relevant Research Ethics Committee.

    Modification category What it covers Typical regulatory action
    Substantial modification Changes likely to affect participant safety, physical or mental integrity, or the scientific value of the trial Full MHRA and/or REC review before implementation
    Modification of an important detail Changes to trial conduct that fall short of “substantial” but still need regulatory visibility Notification-based route, streamlined against the 2004 regime
    Minor modification Administrative or low-impact changes with no bearing on safety or scientific validity Recorded rather than formally reviewed

    Research Ethics Committees have also been restructured to align with ICH-GCP E6: each REC must now have at least five members with the collective expertise to assess a trial’s scientific, medical and ethical aspects, must retain an appointed Chair, and must include at least one lay member.

    Transparency duties and the transition timeline

    For the first time, UK law requires sponsors of CTIMPs to register their trial in a public registry, publish a summary of results within 12 months of trial completion, and offer participants a summary of results in an accessible format (with limited deferral provisions, for example for Phase 1 healthy-volunteer studies). This closes a long-standing transparency gap that UK research bodies had previously addressed only through voluntary commitments.

    The reform followed a multi-year statutory process, set out below.

    Date Milestone
    March–April 2022 Public consultation on proposed reforms
    December 2024 Statutory Instrument laid before Parliament
    February 2025 Approved by the Westminster Parliament and House of Lords
    April 2025 Northern Ireland Assembly approval and final ministerial sign-off; 12-month implementation period begins
    June–October 2025 HRA and MHRA guidance published and finalised
    28 October 2025 Six-month countdown to implementation
    28 April 2026 Amended regulations and UK ICH E6(R3) GCP come into force

    Diversity and public involvement remain guidance-led rather than statutory. The HRA’s Public Perceptions of Research work found that 88% of respondents believe trials should involve a diverse group of participants, 70% support this even where it increases cost, and 74% support it even where it extends timelines — evidence the HRA and MHRA cite in the (non-legal) inclusion and diversity guidance now being piloted alongside the statutory reforms.

    Answer-first Q&A

    What are the UK clinical trial regulations?

    The UK clinical trial regulations are the Medicines for Human Use (Clinical Trials) Regulations 2004, as amended by the 2025 Regulations in force from 28 April 2026. They govern authorisation, ethical review, conduct, safety reporting and transparency for CTIMPs across all four UK nations, jointly overseen by the MHRA and HRA-recognised Research Ethics Committees.

    What is the regulatory body for clinical trials in the UK?

    The Medicines and Healthcare products Regulatory Agency (MHRA) authorises and inspects clinical trials of medicines, while the Health Research Authority (HRA) coordinates Research Ethics Committee review, most commonly through the Combined Review service that gives sponsors a single joint application route for both bodies.

    What are the regulatory requirements for clinical trials in the UK?

    Sponsors must obtain MHRA authorisation and REC approval, correctly classify each modification as substantial, important-detail or minor, register the trial in a public registry, recruit a first participant within two years of approval, and publish a results summary within 12 months of trial completion.

    What research offices must do now

    With the transition period closed, institutional research offices, sponsors and trial teams need to move from preparation to operation. Priority actions include:

    • Update standard operating procedures, protocol templates and delegation logs to use the new terminology — “modification” not “amendment”, “participant” not “subject”, “trial location” not “trial site”.
    • Retrain staff who classify trial changes, since misclassifying a substantial modification as minor risks a compliance breach with the MHRA or REC.
    • Confirm registry and results-publication workflows exist and are resourced, given the new 12-month statutory deadline for posting result summaries.
    • Check that any Clinical Trial Agreement in use is the current mCTA version, and flag legacy templates for replacement.
    • Build recruitment-milestone tracking into trial management systems so the two-year first-participant deadline — and any extension request — is never missed.
    • Review whether qualifying low-intervention studies can adopt the simplified consent arrangements, and update ethics submissions accordingly.

    Research administration offices coordinating these changes across multiple trials and faculties may find it useful to revisit institutional research administration workflows and governance documentation as part of this update, since the reform touches sponsorship, contracting and compliance functions simultaneously rather than a single office alone.

    Outlook: bedding in the new regime

    The MHRA and HRA have signalled this is implementation, not a one-off event: guidance will continue to be refined, including on Phase 1 healthy-volunteer trials, diversity and inclusion, and public involvement, none of which are statutory requirements but all of which the regulators expect sponsors to engage with. Early inspection and audit activity through 2026 and 2027 will show how consistently the risk-proportionate approach — and the new modification categories in particular — are applied in practice. Research offices that treat 28 April 2026 as the start of an embedding period, rather than a single compliance deadline already met, will be best placed to avoid later remediation.

  • NIH Grant Application Cap: What Changed and Why

    The NIH grant application cap is no longer a single rule. Since September 2025, principal investigators (PIs) have faced a firm limit on how many applications they can submit each year. As of June 2026, NIH is now consulting on a second, separate limit — this time on how many grants a PI can hold at once. The two policies are frequently conflated in coverage, but they operate on different mechanisms, timelines, and parts of a research office’s workload.

    Two different NIH caps, explained

    The first cap is already in force. Effective 25 September 2025, NIH limits each principal investigator (PI) or multiple-PI (MPI) team member to a maximum of six new, renewal, resubmission, or revision applications per calendar year. The limit applies per PI, not per institution, and resubmissions count toward the total — so a PI who submits three new applications and then resubmits two after a first review has used five of six slots.

    The cap excludes R13 conference grants and T-series training activity codes. Critically for multi-PI labs, it also excludes collaborative submissions where a researcher is listed only as a co-investigator or other senior/key personnel rather than as PI or MPI. NIH told Inside Higher Ed that only 1.3% of applicants submitted more than six PI/MPI applications in 2024 — the vast majority of investigators were never going to be affected by the ceiling itself.

    The second cap is still a proposal. On 8 June 2026, NIH published NOT-OD-26-086, an RFI seeking comment on a policy that would cap the number of simultaneous Research Project Grants (RPGs) a single PI can hold, with options of two, three, or four concurrent awards. This is a portfolio cap, not a submission cap — it would restrict how many active RPGs a PI can run at once, regardless of how many applications they submitted to get there. Science reported that a three-RPG limit was modelled to free roughly $2 billion and support around 3,020 additional investigators, while a two-RPG cap was modelled to free a larger sum, cited at roughly $3.5 billion. The comment period is open until 3 August 2026.

    Feature Submission cap (in force) Concurrent-award cap (proposed)
    Status Active policy since 25 Sept 2025 RFI (NOT-OD-26-086), comments open to 3 Aug 2026
    What it limits Applications submitted per calendar year RPGs held simultaneously per PI
    Threshold 6 applications (new, renewal, resubmission, revision combined) 2, 3, or 4 concurrent RPGs (options under review)
    Excludes R13 conference grants; T-series training codes; co-I/senior-key-personnel roles Not yet finalised
    Stated rationale Reduce review-system overload, curb AI-assisted mass submission Broaden funding distribution across more investigators

    Why NIH is doing this: the portfolio-management rationale

    Both policies are framed by NIH as portfolio-management measures rather than budget cuts. The submission cap arrived alongside a companion policy on AI-generated content: NIH will not treat applications “substantially developed by AI” as original ideas of the applicant, and post-award detection can trigger a referral to the Office of Research Integrity alongside cost disallowance or termination. NIH told reporters the pairing was meant to stop high-volume, AI-assisted submissions from overwhelming peer review — not to reduce the number of investigators it funds.

    The concurrent-award RFI targets a different bottleneck: funding concentration. NIH’s own modelling, reported by Science, suggests a relatively small number of well-funded PIs hold a disproportionate share of active RPGs, and capping simultaneous awards at two, three, or four would redistribute billions toward early- and mid-career investigators who currently hold zero or one RPG — a structural-limit approach also used in eligibility rules at other national funders.

    • The submission cap manages review-system load.
    • The proposed concurrent-award cap manages funding concentration.
    • Neither policy, as currently described, changes the NIH salary cap (set at $228,000 for 2026), which governs allowable reimbursed salary under an award, not how many awards a PI may hold.

    Answer-first: common questions on the NIH grant application cap

    What is the maximum number of applications for NIH?

    Since 25 September 2025, each principal investigator or multiple-PI team member may submit a maximum of six new, renewal, resubmission, or revision applications per calendar year. Conference (R13) and training (T-series) applications are excluded, as are submissions where the researcher is listed only as a co-investigator rather than PI or MPI.

    What is the new NIH cap for 2026?

    There are two distinct 2026 developments, and they are easily confused with the unrelated NIH salary cap ($228,000 for 2026). The application-submission cap (six per year) took effect in 2025 and remains active. In June 2026, NIH separately opened an RFI, NOT-OD-26-086, proposing to cap how many concurrent RPGs a single PI may hold, with comments due by 3 August 2026.

    Does the application cap include co-investigators and multi-PI teams?

    No. The six-application limit counts applications where a researcher is listed as PI or MPI. Collaborative submissions naming a researcher only as a co-investigator or other senior/key personnel do not count toward that individual’s cap, which is the main structural workaround available to multi-PI labs today.

    When does the NIH RFI comment period close?

    The public comment period for NOT-OD-26-086, the proposal to cap concurrent RPGs per PI, closes on 3 August 2026. Institutions, scientific societies, and individual investigators can submit input directly to NIH before that deadline, ahead of any final policy decision.

    Practical workarounds for multi-PI labs

    Research administrators advising multi-PI groups have several concrete levers under the current (submission-cap) rules:

    • Restructure authorship roles deliberately. Only PI/MPI-listed applications count toward the cap, so labs with more ideas than headroom can route some proposals through a co-investigator or senior/key personnel role for researchers who have used their six slots.
    • Sequence resubmissions carefully. Resubmissions count toward the same total as new submissions, so a PI planning two new R01s and a resubmission must track all three against the ceiling from the start of the cycle, not treat resubmission as “free”.
    • Front-load the strongest applications. With a hard ceiling of six, strategy shifts from “submit broadly” toward prioritising the highest-confidence proposals for limited PI/MPI slots, using non-PI collaborative roles for higher-risk ideas.
    • Track activity codes against the exclusion list. R13 conference grants and T-series training awards fall outside the cap entirely; labs running these should confirm applications aren’t wrongly counted against the six-application limit.
    • Watch the RFI, not just the final rule. With the concurrent-award cap open for comment until 3 August 2026, institutions with PIs holding three or more active RPGs have a narrow window to model exposure before any threshold is finalised.

    Implications for institutions and research offices

    For sponsored-programmes offices, the practical burden shifts from “how many can we submit” to “how do we allocate scarce PI slots.” Portfolio dashboards need to track each PI’s six-application count in real time, since resubmissions and revisions from earlier in the year silently consume capacity. It also raises internal equity questions: early-career PIs who have not yet hit historical submission volumes are effectively unconstrained, while a small number of high-output senior PIs may need support prioritising which six applications matter most.

    If the concurrent-award cap is adopted, the implication is larger still. Research offices would need to model which currently-funded PIs already exceed a prospective two-, three-, or four-RPG ceiling, and plan succession — including early-career co-investigators who could be elevated to PI on a renewal. Both policies also interact with the NIH Grants Policy Statement’s existing budget-deviation rules, under which cost-category deviations of 25% or more from an approved budget may require prior sponsor approval; institutions restructuring PI roles to manage the cap should route resulting scope changes through that existing mechanism.

    What’s next

    The six-application submission cap is settled policy, unlikely to be revisited before NIH gathers a full year of compliance data. The concurrent-award RFI is the item to watch: with comments open until 3 August 2026 and modelled effects ranging from roughly $2 billion (a three-RPG limit) to roughly $3.5 billion (a two-RPG limit) in redistributed funding, the threshold NIH eventually chooses will materially change how research-intensive institutions structure PI status on renewals. Research administration offices tracking funder-mandate changes should treat the comment period as an active planning window, not a wait-and-see notice — the final policy is likely to arrive with limited transition time once published.

  • UKRI Policy Fellowships 2026: Embedding Researchers in Government

    What are the UKRI Policy Fellowships 2026

    UK Research and Innovation opened its 2026 call on 9 June 2026, and the UKRI Policy Fellowships 2026 now offer 50 embedded fellowship positions across 26 host partners spanning UK government departments, devolved administrations, arm’s-length bodies and the What Works Network. Each fellowship runs for 18 months and places a researcher directly inside a policy team, working alongside civil servants on live evidence needs rather than producing research at arm’s length.

    The scheme sits within UKRI’s wider fellowship investment framework, which funds researcher mobility between academia and non-academic settings. Unlike a conventional secondment negotiated bilaterally between a university and a government department, the policy fellowships route is a competitive, centrally administered funding call with fixed strands, published cost ceilings and a standard exemplar agreement — details that matter as much to research offices as to the applicants themselves.

    Applications close at 16:00 on Thursday 10 September 2026, submitted through the UKRI Funding Service by the applicant’s employing research organisation.

    Funding strands, amounts and cost-sharing

    The 2026 call is organised into three funding strands, each with its own focus, eligible career stage and full economic cost (FEC) ceiling. UKRI funds 80% of the FEC; the remaining 20% is met by the fellow’s employing research organisation, consistent with the standard UKRI research grant cost-sharing model rather than a fully funded secondment.

    Strand Focus FEC ceiling Career stage
    Core Policy Fellowships Priority areas across UK and devolved government Up to £180,000 Early or mid-career
    What Works Innovation Fellowships Homelessness, policing and place, via the What Works Network Up to £220,000 All career stages
    Natural Hazards and Resilience Fellowships System resilience and preparedness for environmental risk Up to £280,000 Early or mid-career

    Host partners named against these strands include the Department for Business and Trade, the Ministry of Housing, Communities and Local Government, the Scottish Government, the Department of Health and Social Care, the UK Health Security Agency, the Ministry of Justice, the Home Office, the Department for Education, the Cabinet Office, the Environment Agency, the Centre for Homelessness Impact and the Wales Centre for Public Policy, among others. Thematic clusters span economic growth and industrial strategy, health inequalities, justice and public safety, education, housing and place, and the use of data and AI in government.

    Eligibility, key dates and how to apply

    Applicants must hold a doctorate or equivalent research experience, be based at a UKRI-eligible research organisation, and demonstrate subject-matter expertise relevant to a specific fellowship position. UKRI is explicit that career stage is not time-bound by years since doctorate; a researcher without a PhD may still qualify if they can evidence an equivalent sustained research-focused role. Researchers who have already undertaken or are currently undertaking a UKRI policy fellowship are not eligible to reapply.

    • Call opened: 9 June 2026, 09:00
    • Applicant webinar: 25 June 2026
    • Deadline: 10 September 2026, 16:00
    • Shortlisting: October to November 2026
    • Interviews: January 2027
    • Decisions: February 2027
    • Fellowship start: 1 May 2027

    Only the lead research organisation can submit an application to UKRI, though the fellowship agreement itself is negotiated between three parties: the host partner, the fellow, and the employing research organisation. Fellows must also pass any security, nationality and clearance checks the specific host requires before the placement can begin.

    What is the deadline for UKRI Policy Fellowships 2026?

    Applications for the UKRI Policy Fellowships 2026 close at 16:00 on Thursday 10 September 2026, submitted via the UKRI Funding Service. Only the applicant’s lead employing research organisation can make the submission, so institutional sign-off must be secured well before this deadline.

    Who is eligible to apply for UKRI policy fellowships?

    Eligible applicants hold a doctorate or equivalent research experience, are based at a UKRI-eligible research organisation, and meet the early or mid-career descriptor for Core Policy and Natural Hazards strands. What Works Innovation Fellowships are open to researchers at all career stages, including those without a completed doctorate.

    How many UKRI policy fellowship positions are available in 2026?

    UKRI is funding 50 fellowship positions across 26 host partners in the 2026 call, spanning UK government departments, devolved administrations, arm’s-length bodies and What Works Network members. Positions are distributed unevenly across the three funding strands and named host organisations.

    How is UKRI policy fellowship funding structured?

    UKRI funds 80% of the full economic cost of each fellowship, up to strand-specific ceilings of £180,000, £220,000 or £280,000. The employing research organisation covers the remaining 20%, matching UKRI’s standard grant cost-sharing model rather than a fully externally funded secondment.

    How research offices administer secondment agreements and reporting

    For research administrators, the operational detail sits below the headline figures. UKRI requires a formal fellowship or secondment agreement between the host partner, the fellow and the employing research organisation before a placement starts. UKRI has published an exemplar agreement, developed in consultation with UKRI Legal, central government departments and the university sector, and advises institutions to review it well ahead of submission rather than treating it as a post-award formality.

    This has direct implications for how institutions resource the administration of placement schemes:

    • Costing and 20% co-funding sign-off: Because UKRI funds only 80% of FEC, finance teams must confirm the department or faculty can cover the balance before the application is submitted, not after the award is made.
    • Compliance checks: UKRI states plainly that research office and finance teams undertake checks on hosting arrangements and financial eligibility, while ultimate responsibility for compliance remains with the applicant — a split of accountability research offices should document in their own sign-off workflow.
    • Host-specific clearance: Security and nationality checks vary by host department, so administrators cannot rely on a single institutional template; each placement’s clearance requirements need checking against the specific host’s published criteria.
    • Mentor and team roles: Early-career applicants must name a senior mentor from their employing organisation, adding a role that research offices need to track alongside the fellow and the host contact.
    • Reporting during placement: Fellows remain employed by their home institution throughout, so payroll, HR and reporting lines stay with the research organisation even while day-to-day line management sits with the host — a dual-reporting structure that research administration systems must be configured to reflect.

    This three-way agreement structure — host, fellow, employer — is the genuine administrative distinction of the UKRI scheme compared with informally negotiated academic-government exchanges, and it is the detail most coverage of the 2026 call omits in favour of headline position and funding counts.

    Implications for institutions and applicants

    Research offices supporting an applicant should treat the fellowship agreement review as a parallel workstream to the academic proposal, not a downstream task. Given the FEC ceilings scale with strand rather than individual placement complexity, institutions should also confirm early whether their standard overhead recovery models accommodate an 80/20 split embedded within a government host, rather than a conventional university-based grant.

    Applicants working with sensitive or linked administrative datasets should note that feasibility assessments — including secure data access approvals — need to be scoped against the 18-month fellowship window from the outset, since data access timelines can otherwise outrun the placement itself.

    Outlook: what happens after the September deadline

    With shortlisting running October to November 2026, interviews in January 2027 and a fellowship start date of 1 May 2027, institutions have a multi-month gap between submission and confirmed placement — a window research offices can use to finalise co-funding approvals, mentor arrangements and host-specific clearance paperwork rather than leaving them until decisions land. As UKRI continues to expand policy fellowship strands beyond their original remit, research administrators are likely to see this three-party agreement model applied to further embedded-researcher schemes, making early familiarity with the exemplar agreement a transferable skill rather than a one-off task.

  • NIH Grant Terminations in 2026: What Was Cancelled, What Was Restored, and Why

    What happened: the 2025-2026 NIH termination wave

    Beginning in March 2025, the National Institutes of Health cancelled thousands of active research awards in one of the largest disruptions to federal biomedical funding in decades. A peer-reviewed analysis published in the Proceedings of the National Academy of Sciences in 2026 counted 2,291 active NIH research grants terminated in the initial wave, withdrawing an estimated $2.45 billion in committed funding. NIH grant terminations continued through the spring, and by late May 2025 Harvard T.H. Chan School of Public Health researchers tracking the cuts put the cumulative total at roughly 2,100 grants worth approximately $9.5 billion.

    Independent counts diverged because institutions and awarding offices reported figures at different points in a fast-moving process. The Association of American Medical Colleges recorded 777 terminated grants representing $1.9 billion as of 5 May 2025, while an implementation-science analysis published in PubMed Central counted 702 terminations as of 5 April 2025. The variance reflects the pace of the cuts rather than disagreement about their occurrence.

    Which grants and research topics were targeted

    Termination notices sent to grantees cited a shift in agency funding priorities away from topics the administration characterised as “unscientific” or as promoting discrimination. Research areas disproportionately affected included:

    • LGBT+ health and gender-identity research
    • Diversity, equity, and inclusion (DEI) initiatives in the biomedical workforce
    • Vaccine hesitancy and confidence studies
    • Health equity and racial health-disparities research
    • Climate change and environmental-health research

    Reporting by Applied Clinical Trials Online found that 20% of terminated grants were early-career training awards, a category central to sustaining the biomedical research pipeline. A subsequent analysis found the cuts fell disproportionately on Black, Indigenous, and other minority researchers, as well as investigators from sexual and gender-minority communities — a pattern that later became central to the legal challenges against the terminations.

    Court-ordered restorations: the timeline

    Multiple lawsuits challenged the terminations as procedurally unlawful and discriminatory. The table below summarises the major rulings tracked through mid-2026.

    Date Ruling / event Outcome
    16 June 2025 Judge William Young (D. Mass.), APHA v. NIH Ordered NIH to restore 367 grants worth nearly $3.8 billion; found the termination process “arbitrary and capricious” and discriminatory toward LGBTQ-related research
    25 June 2025 NIH response to court order NIH ceased issuing new terminations of “politically sensitive” grants while the ruling was contested
    August 2025 Federal court order, UCLA class action Ordered restoration of NSF grants suspended at UCLA from 1 August 2025
    September 2025 Federal court order, UCLA Ordered restoration of NIH funding suspended at UCLA from 31 July 2025; NIH reinstated the awards
    May 2026 Ninth Circuit Court of Appeals Upheld reinstatement of grants terminated under DEI- and environmental-justice-related executive orders, the first major appellate ruling on the issue

    The Department of Health and Human Services has pursued appeals against several of these rulings, so the restoration list is not static. Institutions should treat any given month’s figures as a snapshot rather than a final count.

    Answer-first: common questions about NIH grant terminations

    How many NIH grants have been terminated?

    Counts vary by source and date because the terminations rolled out over several months. Published figures range from 702 grants in early April 2025 to 2,291 grants worth $2.45 billion in the fullest peer-reviewed accounting, published in PNAS in 2026.

    Have any terminated NIH grants been restored?

    Yes. A federal judge ordered 367 grants restored in June 2025 following the APHA v. NIH ruling, and separate court orders restored NIH and NSF funding to UCLA researchers later that year. In May 2026 the Ninth Circuit Court of Appeals upheld further reinstatements.

    How can a research office check if a specific NIH grant was terminated?

    Research offices should cross-check award numbers against NIH RePORTER, the HHS TAGGS terminated-grants list, and USASpending.gov, then corroborate against the crowdsourced Grant Watch database, which aggregates termination notices submitted directly by affected principal investigators.

    What is the Grant Watch database?

    Grant Watch is an independent tracker built by Harvard T.H. Chan School of Public Health researcher Scott Delaney and computational researcher Noam Ross, combining government data with crowdsourced submissions to document NIH and NSF grant terminations that agency reporting has not consistently disclosed.

    Monitoring exposure: RePORTER, TAGGS, and tracker databases

    For sponsored-programmes offices, the operational question is not just what happened nationally but which of an institution’s own awards are exposed. No single federal system currently gives a real-time, authoritative picture of terminations and restorations together, so offices need to triangulate across sources.

    Tool Custodian Best for
    NIH RePORTER National Institutes of Health Authoritative award status, PI, institution, and funding history lookups
    HHS TAGGS (terminated-grants list) U.S. Department of Health and Human Services Official, periodically updated PDF/CSV of terminated HHS awards by agency
    USASpending.gov U.S. Treasury / OMB Government-wide obligation and de-obligation records across all federal awards
    Grant Watch Independent researcher-run project Early, crowdsourced signal on terminations before official lists update

    A practical monitoring routine for a research office includes:

    1. Reconcile the institution’s active award list against NIH RePORTER monthly, flagging any status changes.
    2. Cross-check flagged awards against the HHS TAGGS terminated-grants file for confirmation of formal termination.
    3. Monitor Grant Watch and institutional legal counsel updates for early warning and litigation status, since court-ordered restorations can lag or precede official RePORTER updates.
    4. Maintain a standing register of affected PIs so restoration notices — which are sometimes issued quietly — are not missed.

    Because restorations have followed litigation rather than routine agency process, research offices that rely solely on award letters risk missing reinstatements that require the institution to formally re-accept funding within a compliance window. Building this monitoring into research administration workflows, rather than treating it as a one-off compliance exercise, is now a standing requirement for institutions with federally funded portfolios.

    Implications for institutions, PIs, and research offices

    The termination-and-restoration cycle has practical consequences beyond the immediate funding gap. Institutions have had to decide whether to bridge-fund affected projects, hold staff and data-collection activities in limbo, or wind down studies that may later be reinstated. Early-career researchers, who held a disproportionate share of terminated training awards, face particular career risk from even temporary funding gaps.

    The pattern of litigation-driven reinstatement also means compliance offices cannot treat a termination notice as final without checking litigation status — a departure from how terminations were historically administered. As appellate rulings such as the May 2026 Ninth Circuit decision accumulate, research offices should expect further reinstatements to arrive on a rolling basis rather than as a single resolution, making ongoing monitoring — not a one-time audit — the operationally necessary posture through the remainder of 2026.