
Undisciplined
Future models of funding and evaluating transdisciplinary research [completed]


Future models of funding and evaluating transdisciplinary research [completed]

Research funding landscape analysis

RoRI Atlas of Peer Review

Advancing Research on Research Use to Enhance Positive Impact

The uses and evaluation of researchers’ narrative CVs

Translating Publish-Review-Curate outputs into actionable signals for research funders: A MetaROR Study


A study of cumulative advantages in funding allocation [completed]

Getting responsible about AI and machine learning in research funding and evaluation [completed]

A Secure Collaboration Hub for Metascience

Exploring gender inequality in research funding

New geographies of research assessment
Getting responsible about AI and machine learning in research funding and evaluation
Artificial intelligence (AI) is transforming research systems around the world. Research funders have a central role in enabling new AI innovations, but they are also increasingly AI users: as global research funding and assessment become more data-driven, funders are exploring the use of AI and machine learning to better leverage their deep knowledge and extensive data about the research sector.

A UK funder study of potential uses of AI in national research evaluation sparked debate in the journal Nature.
The GRAIL project is developing the new knowledge, evidence, and practical guidance to help ensure that research funders are equipped to use AI effectively, ethically, and equitably in research funding and assessment. GRAIL has three core workstreams:
In 2021, RoRI and the Research Council of Norway co-hosted a series of three virtual workshops on the use of AI and machine learning (AI/ML) technologies in research funding and evaluation.
Those workshops, summarised in a 2022 joint RoRI/RCN Working Paper, highlighted the need for developing clear, practical shared understanding of the potential roles of AI/ML technologies for research funders, and how funders could go about using these tools effectively, ethically, and equitably.
The GRAIL project responds to this need with three in-depth work streams:
Research funders around the globe have been experimenting with AI and machine learning in their own organisations, but funders often lack opportunities to learn from each other, share successes, and solve common problems.
To close this gap, the GRAIL project has been built around a cross-funder workshop series including twelve focused discussions over two years. GRAIL workshops are coproductive spaces in which funders come together to discuss a particular use case for AI/ML or how to tackle a specific practical challenge in using technologyAI/ML within their own organisations.
GRAIL workshops offer a much-needed space for research funders to exchange knowledge and experiences with AI, while building a shared base of practice to support new applications.
To better support future uses of AI/ML in research funding and assessment, GRAIL is conducting the first data collection on current AI/ML applications by funders.
In partnership with RoRI’s AGORRA project, we collected data on AI/ML applications in research assessment from funders around the world, as part of the Global Research Council 2025 survey on responsible research assessment. Our findings, including organisational perspectives on managing AI/ML processes in practice, are published in the 2025 GRC report.
We are also working with our global consortium of funders in GRAIL to collect detailed examples of AI/ML use cases in research funding processes, illustrating the diverse purposes AI/ML are being put to and the challenges involved in responsible use.
The GRAIL project aims to ensure that future applications of AI/ML technologies by research funders are as well-informed as possible and build on a shared base of good practice. To facilitate this, we are producing a handbook on responsible use of AI and machine learning for research funders, as a go-to reference for funders and others in research systems.
Funding by Algorithm is launching in June 2025, and addresses a wide range of key knowledge for AI/ML use in funding contexts:
GRAIL runs from April 2023 – June 2025.
The GRAIL workshop series included twelve workshops between June 2023 – April 2025:
Data collection on AI in research assessment:
Data collection on AI in research funding: internal to funders participating in GRAIL; our survey has run from September 2024 – May 2025.
Funding by Algorithm was developed September 2024 – April 2025, and will be published June 2025.
A handbook for responsible uses of AI and machine learning by research funders
Funding by Algorithm was launched as a diamond open-access publication by RoRI in June 2025. The handbook includes the following sections:
AI and Reviewer Matching in Research Funding
Three case studies exploring how funders are using AI to match grant applications with reviewers.

Key lessons, guidance and directions from the GRAIL project
We publish timely essays, reflections and signals from across metascience, research policy and reform. Expect original thinking, reactions to live debates, and practical insights from people studying research.