CASRAI Dictionary

Tag: government grants management function

  • AI in Research Administration: Where It’s Actually Deployed

    Most coverage of artificial intelligence in higher education still centres on the classroom — chatbots writing essays, detectors chasing them. Less visible, but arguably more consequential for research offices, is AI in research administration: the back-office layer of proposal budgeting, compliance screening and post-award reporting that keeps federally and privately funded research compliant and auditable. That layer is where AI is quietly moving from pilot to production in 2026, and the evidence — not the marketing copy — shows a narrower, more cautious footprint than headlines suggest.

    This is not a piece about generative AI and authorship integrity, disclosure norms, or research misconduct detection in manuscripts — those questions sit in a separate, already well-documented debate. This is about the administrative machinery: proposal-budget checking, risk-based compliance review, contract redlining and financial reporting inside research offices, sponsored-programmes units and grants-management systems.

    Where AI Is Actually Being Deployed

    The clearest signal comes from a March 2026 Ithaka S+R report, funded through the National Science Foundation’s GRANTED programme (grant #2437518), which convened two workshops — one at Montclair State University (31 participants, 13 institutions) and one at Chapman University (32 participants, 13 institutions) — specifically to catalogue how research administration software and AI tools are being used inside research offices. The findings map closely onto three workflow areas:

    • Pre-award proposal and budget checking. Institutions are using AI to review draft proposals and budgets for items that will trigger downstream review — facilities requirements, human-subjects protocols, or budget lines inconsistent with a sponsor’s rules.
    • Risk-based compliance screening. AI is used as a first-pass filter that flags transactions, contract clauses, or expenditures for human review rather than replacing that review — described by workshop participants as “an extra layer” that directs attention, not a decision-maker.
    • Contract and reporting automation. Redlining of routine contract language, drafting of progress narratives, and identification of funded projects with commercialisation potential are the most cited post-award use cases.

    Two concrete examples illustrate the pattern at very different institutional scales. Southern Utah University, a smaller teaching-focused institution, built a budget-availability report that automatically flags high-risk expenditures for review — a narrow, operationally specific tool rather than a platform. At the University of California San Diego, a large research-intensive institution, the contracts and grants office is running risk-based proposal review to identify projects needing facilities or IRB attention, and has automated non-disclosure-agreement redlining in a way staff estimate cuts drafting time by roughly 70 percent.

    Workflow stage AI use case Maturity in 2026 Reported example
    Pre-award Proposal/budget risk flagging Early production UCSD risk-based proposal review
    Pre-award Funding-opportunity matching Experimental Faculty-to-grant matching pilots
    Compliance Contract clause / NDA redlining Early production UCSD NDA redlining
    Compliance Expenditure anomaly flagging Pilot Southern Utah University budget-availability tool
    Post-award Progress-report drafting Experimental Institution-reported pilots, Ithaka S+R 2026
    Institution-wide Policy Q&A chatbot for staff Early production UCSD TritonGPT; Emory ORAgpt proof-of-concept

    Evidence From the Field: What Institutions Report

    Two enterprise-level projects sit ahead of the field. TritonGPT, developed at UC San Diego and trained on institutional policy documents, has been available to the campus community since 2023 and is now offered as software-as-a-service to other institutions. At the University of Idaho, the NSF GRANTED-funded AI4RA initiative is building open-source tools for research administrators. At the system level, the California State University system ran a 94,000-response AI sentiment survey — described as the largest of its kind — to set baseline metrics before committing to further rollout.

    These are not isolated enthusiasm projects. The Council on Governmental Relations (COGR) has documented that the U.S. federal government issued more than 200 new or revised policies affecting research administration over the preceding ten years — a compliance burden that is the actual driver behind AI adoption, not novelty. Emory University’s sponsored-programmes office built a proof-of-concept generative AI chatbot, reported by SRA International in May 2025, intended to give research administrators instant, policy-grounded answers rather than requiring them to search static guidance documents.

    Answer-First Q&A

    What is AI actually used for in research administration?

    Institutions report using AI mainly for risk-based screening: flagging proposal budgets, contract clauses, or expenditures that need human review, plus drafting routine reports and answering staff policy questions. It is deployed as a triage layer, not as an autonomous decision-maker in compliance-sensitive workflows.

    Is AI reliable enough for research compliance work?

    Not on its own. Workshop participants in the Ithaka S+R study described current tools as error-prone for high-stakes compliance decisions, so institutions keep a human reviewer in the loop and use AI outputs as a prioritisation signal rather than a final determination.

    What is electronic research administration (eRA) software?

    Electronic research administration (eRA) software centralises pre-award proposal development, post-award financial tracking, IRB/IACUC compliance management, and reporting in one system. Vendors including Cayuse, InfoEd Global and Streamlyne are now embedding AI features into these existing platforms rather than institutions building AI tools separately.

    Will AI replace research administrators?

    Current evidence points the other way. Institutions describe AI as freeing staff time for relationship-building and strategic work, while raising a genuine concern: if entry-level document review and compliance checks are automated away, the profession may lose the training ground that builds administrator judgement over time.

    What Remains Experimental — and Why

    Effort-report anomaly detection — using AI to flag inconsistencies in how research staff certify time charged to federal awards — is frequently proposed as a logical extension of risk-based screening, but publicly documented institutional deployments remain scarce as of mid-2026. This gap matters: effort reporting sits inside some of the most tightly regulated financial-compliance territory in federally sponsored research, and institutions appear to be moving deliberately rather than rushing tools into that specific workflow.

    Three barriers recur across every institution surveyed in the Ithaka S+R workshops:

    • Data governance. Fragmented, inconsistent institutional data undermines AI output quality, and grant proposals routinely contain data covered by HIPAA, export-control rules, or pre-publication intellectual property.
    • Fragmented adoption. Most institutions have not articulated an institution-wide AI strategy for research administration; use is left to individual staff discretion, producing uneven, hard-to-scale experimentation.
    • Trust. Faculty scepticism about whether proposal or compliance data will be used to train external vendor models directly affects whether research administrators can deploy AI tools without damaging working relationships they depend on.

    Implications for Institutions and the Profession

    The practical pattern for institutions considering AI in grants management and compliance workflows is narrower and more disciplined than vendor marketing implies: start with a specific, bounded use case — budget flagging, contract redlining, a policy-guidance chatbot — evaluate it against defined return-on-investment questions, and keep a human reviewer accountable for the final determination. The institutions cited above succeeded by treating AI as an attention-directing layer inside existing research administration workflows, not as a replacement for the judgement that compliance work requires.

    For the broader field of research management and administration, the open question the Ithaka S+R researchers themselves flag is workforce development: if AI absorbs the entry-level document review that has historically trained new research administrators, institutions will need to redesign how professional judgement is built, not just how workloads are reduced. Organisations such as NCURA, SRA International and NORDP are already the venues where this cross-institutional knowledge-sharing is happening, ahead of any formal standard for AI use in the field.

    CASRAI’s own coverage of research administration software categories and standards tracks how eRA platforms are evolving as AI features are absorbed into existing pre-award, post-award and compliance modules — the practical mechanism by which most institutions will encounter AI in this space, rather than through bespoke in-house builds.

  • Grant Administration vs Grant Management: A Research-Office Guide

    A sponsored programmes office in a university, hospital trust, or research institute rarely has the luxury of clean job titles. Staff are asked to do “grants work” without anyone specifying which of two genuinely different functions they mean. Grant administration vs grant management is not a semantic quibble — it maps onto two distinct phases of the funding lifecycle, with different skills, different risk profiles, and different reporting lines. Getting the distinction right affects how research offices staff themselves, how they onboard new starters, and how they explain their own structure to auditors and funders.

    This explainer sets out the practical difference, shows where each function sits against the pre-award/post-award lifecycle, and answers the questions research administrators most commonly search for when trying to draw the line.

    What is grant administration?

    Grant administration is the compliance-facing, largely post-award function. It exists to make sure that once money has been awarded, it is spent, tracked, and reported exactly as the funder’s terms and conditions require. Grant administrators are the people who keep an award audit-ready from the moment funds land to the moment the final financial report is submitted.

    Typical grant administration duties include:

    • Setting up the award in the institution’s financial system and reconciling it against the signed agreement
    • Monitoring budget lines, allowable costs, and cost transfers against the approved grant budget
    • Tracking effort reporting, cost-sharing commitments, and indirect cost (overhead) recovery
    • Preparing and submitting financial and progress reports on the funder’s schedule
    • Managing award amendments, no-cost extensions, and close-out procedures

    In US institutions this work is typically anchored to the Uniform Guidance (2 CFR 200) and individual agency terms from bodies such as NIH and NSF. In the UK, the equivalent compliance backbone runs through UKRI’s grant terms and conditions, institutional TRAC (Transparent Approach to Costing) returns, and Research England reporting requirements. The regulatory vocabulary differs by jurisdiction; the underlying function — disciplined, rules-bound post-award stewardship — does not.

    What is grant management?

    Grant management is the broader, strategic function that spans the entire lifecycle: identifying funding opportunities, shaping competitive proposals, and — once an award is won — overseeing whether the funded work is actually achieving its research and institutional objectives. Where administration asks “are we compliant?”, management asks “are we winning the right grants, and are they delivering what we promised?”

    Typical grant management responsibilities include:

    • Scanning funder calls and matching them to institutional and departmental research priorities
    • Supporting principal investigators with proposal development, budget justification, and costing
    • Building and maintaining relationships with programme officers and funder liaison staff
    • Monitoring project performance against milestones, outputs, and outcomes — not just spend
    • Feeding lessons from completed awards back into future bid strategy

    A grant manager’s remit therefore extends well beyond a single award. Many sponsored programmes offices structure this as a “grants management cycle” — pre-award identification and proposal support, award negotiation, post-award delivery oversight, and closeout evaluation that feeds the next cycle.

    Pre-award vs post-award: mapping the responsibilities

    The cleanest way to separate the two functions is against the pre-award/post-award split that most research administration offices already use to structure their teams. Grant management is lifecycle-wide; grant administration is concentrated in — though not exclusively confined to — the post-award phase.

    Dimension Grant administration Grant management
    Primary lifecycle stage Post-award Pre-award through closeout
    Core question Are we compliant with the award terms? Are we funding — and delivering — the right work?
    Typical tasks Budget monitoring, cost transfers, financial reporting, audit readiness Opportunity scanning, proposal development, performance evaluation, funder relationships
    Risk focus Regulatory and financial non-compliance Strategic misalignment, missed opportunities, weak outcomes
    Reference frameworks (illustrative) Uniform Guidance (2 CFR 200), UKRI grant terms, TRAC Institutional research strategy, funder mission fit, ARMA/EARMA/NCURA practice guidance

    In practice, smaller research offices often collapse both functions into a single “research administrator” or “grants officer” role covering the full sponsored research administration remit. Larger institutions tend to separate them, with pre-award research administration and post-award research administration teams sitting either side of the award-negotiation handover point.

    Common questions on grant administration vs grant management

    What is the difference between a grant administrator and a grant manager?

    A grant administrator is primarily responsible for post-award compliance — budget monitoring, financial reporting, and adherence to funder terms. A grant manager oversees the fuller grant lifecycle, including opportunity identification, proposal strategy, and performance outcomes, though in smaller teams one person often holds both responsibilities.

    Is administration higher than management?

    Not in the grants context specifically. Generically, “administration” can refer to policy-setting and “management” to implementation, but within sponsored programmes offices the two are parallel functions — compliance-focused versus strategy-focused — rather than a strict seniority hierarchy. Either role can sit at director level depending on institutional structure.

    What is grant administration?

    Grant administration is the post-award compliance function that ensures grant funds are spent, tracked, and reported according to the funder’s contractual terms. It covers financial oversight, effort reporting, cost-transfer approval, and the preparation of interim and final reports to the awarding body.

    What is the grants management cycle?

    The grants management cycle is the recurring sequence of opportunity identification, proposal development, award negotiation, post-award delivery, monitoring, and closeout evaluation. Lessons from closeout typically feed back into the next round of opportunity identification, making it a continuous rather than linear process.

    Why the distinction matters for research offices

    Blurring grant administration and grant management has real operational costs. Institutions that treat the two as interchangeable often end up with compliance gaps — a research office focused entirely on winning new awards can miss cost-transfer deadlines or effort-reporting certifications, triggering audit findings. Conversely, an office staffed only with compliance-minded administrators can under-invest in the proposal development and funder-relationship work that keeps the award pipeline healthy.

    Professional bodies on both sides of the Atlantic reflect this split in how they organise practice guidance and training. NCURA (US) and EARMA and ARMA (UK/Europe) both maintain competency frameworks that separate pre-award and post-award skill sets, and INORMS’ Research Management and Administration career framework explicitly distinguishes strategic research management from operational research administration. This is not a CASRAI-specific taxonomy — it reflects how the wider research administration profession itself is organised, and institutions building or restructuring a sponsored programmes office should map roles against it rather than inventing local terminology from scratch.

    The distinction also matters for how institutions define career pathways. A research administration career track built purely on compliance risks losing staff who want strategic exposure; a track built purely on management risks producing officers who cannot pass an audit. The strongest sponsored programmes offices deliberately rotate staff across both functions, or pair a compliance-trained administrator with a strategy-trained manager on the same award portfolio.

    Looking ahead: convergence, not confusion

    As grant management systems increasingly automate routine compliance checks — flagging over-budget cost centres or missing certifications automatically — the administrative workload is shifting from manual reporting toward exception handling and judgement calls. That frees grant administrators to take on more of the performance-monitoring work traditionally associated with grant management, and the two functions are likely to converge further at the operational level even as they remain distinct in scope and risk ownership.

    For research offices building or auditing their own structure, the practical takeaway is not to pick one term over the other but to be explicit about which lifecycle stage — and which risk — each role is actually responsible for. That clarity, more than the job title itself, is what keeps sponsored research compliant, competitive, and well governed.

  • Grants Functional Standard: What UK Funders and Institutions Need to Know

    What Is the Grants Functional Standard (GovS 015)?

    The Grants Functional Standard — Government Functional Standard GovS 015: Grants — is the Cabinet Office document that sets mandatory expectations for how UK central government departments and their arm’s-length bodies (ALBs) design, award, monitor and close out grants. First published in December 2016 and periodically updated since, it applies to any organisation administering grants wholly or partly using Exchequer funding, which in practice includes many universities, research charities, learned societies and sector bodies that receive or pass through public grant money.

    The standard operates on a “comply or explain” basis: bodies within scope must either meet the ten Minimum Requirements or record a documented justification for departing from them. It sits alongside the wider suite of UK government functional standards (covering areas such as finance, commercial and project delivery), which exist to give civil servants and delivery partners a consistent, shared language for governance and assurance.

    The Ten Minimum Requirements

    GovS 015 is operationalised through ten numbered Minimum Requirements, each with its own supporting guidance document published by the Government Grants Management Function (GGMF). Together they cover the full grant lifecycle, from senior accountability through to reconciliation and training.

    Minimum Requirement Focus area
    1. Senior Officer Responsible for a Grant Named senior accountability for each grant scheme
    2. Governance, Approvals & Data Capture Sign-off routes and central grant-data recording
    3. Complex Grants Advice Panel (CGAP) Mandatory referral for high-risk or priority schemes
    4. Business Case Development Rationale, options appraisal and value for money
    5. Competition for Funding Fair, open, proportionate award processes
    6. Grant Agreements Terms, conditions and use of the Model Grant Agreement
    7. Risk, Controls and Assurance Fraud risk, security risk and internal controls
    8. Performance and Monitoring In-year tracking of delivery against milestones
    9. Annual Review and Reconciliation Year-end financial and delivery reconciliation
    10. Training Competency requirements for grant-making staff

    Minimum Requirement 7 — Risk, Controls and Assurance — is the section research administrators should watch most closely, because it is the one most recently amended.

    What Changed in the 21 May 2026 Update

    On 21 May 2026, the Cabinet Office published a revised version of Minimum Requirement 7: Risk, Controls and Assurance. Two substantive changes were made:

    • The language governing Fraud Risk Assessments was strengthened, tightening the expectation that grant-making bodies produce and evidence a documented fraud risk assessment as part of the standard’s risk-management requirements.
    • A new paragraph (paragraph 23) was added to provide further guidance on security risk, extending the section’s scope beyond financial and delivery risk to explicitly cover security considerations in grant-funded activity.

    This update did not change the ten-requirement structure of GovS 015 itself; it refined the assurance expectations sitting underneath Minimum Requirement 7. It follows a pattern of incremental, dated revisions the GGMF has made to individual Minimum Requirement documents over recent years — CGAP referral criteria and the Grant Agreements guidance have both been revised on a similar rolling basis. For any body already running a Grants Continuous Improvement Assessment against the standard, the May 2026 wording is the version that self-assessment evidence should now reference.

    Grant Administration, Grant Management and the Centre of Excellence

    GovS 015 sits inside a broader UK government grants ecosystem, and the terminology is often used loosely. It is worth distinguishing the parts precisely, since institutions applying the standard need to know which body owns which function.

    • Grant administration refers to the operational, transactional tasks of running a grant scheme — issuing agreements, processing claims, recording data and reconciling payments.
    • Grant management is the broader discipline: strategic design of a scheme, risk appraisal, performance oversight and continuous improvement, of which administration is one component.
    • The Government Grants Management Function (GGMF) is the cross-government function, hosted by the Cabinet Office, responsible for GovS 015 itself and for coordinating grant-making practice across departments and ALBs.
    • The Grants Centre of Excellence is the operational and advisory capability that supports departments in applying the standard consistently — providing guidance, training and shared services rather than setting the standard itself.

    What is the functional standard for grants?

    It is Government Functional Standard GovS 015, the Cabinet Office document setting mandatory requirements for how UK departments and arm’s-length bodies administer grants funded wholly or partly through the Exchequer. It exists to ensure consistency, regularity and propriety in grant-making and to promote value for money in publicly funded grant schemes.

    What are UK government functional standards?

    Functional standards are Cabinet Office-issued documents that set mandatory (“shall”) and advisory (“should”) expectations for specific government functions — finance, commercial, project delivery and grants among them. They use a shared glossary so departments and their delivery partners work to a common, auditable set of definitions and controls.

    What is the difference between grant administration and grant management?

    Grant administration is the transactional layer — agreements, claims, payments and record-keeping. Grant management is the wider strategic discipline covering scheme design, risk assessment, performance monitoring and continuous improvement, within which administration operates as one supporting activity, not a synonym for the whole function.

    What is the Grants Centre of Excellence?

    It is the cross-government advisory and capability-building resource that helps departments and arm’s-length bodies apply GovS 015 in practice, through guidance, training and shared tools. It supports implementation of the standard; it does not itself author or amend the Minimum Requirements, which remain the responsibility of the Government Grants Management Function.

    Implications for Research-Funded Institutions

    Universities, research charities and sector bodies that receive Exchequer-funded grants — directly from departments or via an ALB — sit within scope of GovS 015 even when they are not themselves a government department. The May 2026 changes to Minimum Requirement 7 have practical consequences for research administration teams:

    • Grant applications and renewals may face closer scrutiny of documented fraud risk assessments, particularly for schemes flagged as complex or high-value.
    • Institutions handling sensitive research areas — dual-use technology, critical infrastructure, or international collaboration — should expect funders to reference the new security-risk paragraph when setting due-diligence conditions.
    • Research offices that already map their processes against Minimum Requirements 1–10 for continuous-improvement self-assessment should update their MR7 evidence base to the 21 May 2026 wording.
    • Grant agreement templates and internal risk registers referencing MR7 should be checked against the current guidance rather than an earlier cached version, since the GGMF revises individual Minimum Requirement documents on a rolling basis rather than reissuing the whole standard.

    None of this changes the fundamentals of good research administration practice — due diligence, documented risk assessment and clear accountability were already core expectations. What changes is the explicitness with which fraud and security risk must now be evidenced under MR7.

    Looking Ahead

    GovS 015 has been revised incrementally rather than replaced outright since 2016, and the pattern is likely to continue: individual Minimum Requirement documents updated as risks evolve, rather than a full standard rewrite. Institutions that treat the standard as a living compliance baseline — checking dated guidance documents against their internal risk frameworks at each award cycle — will be better placed than those that rely on a static PDF saved years ago. For research administrators, the practical takeaway from the 21 May 2026 update is straightforward: fraud risk assessment and security-risk screening are no longer implicit good practice under GovS 015 — they are explicit, documented expectations under Minimum Requirement 7.