Local Government AI Accelerator
New funding scheme supports collaborative research projects between University of Cambridge and local authorities.
The University of Cambridge is launching a new funding scheme to support collaborative AI research and development projects with local government partners. The ai@cam Local Government AI Accelerator will provide grants of up to £25,000 for proof-of-concept projects that address shared challenges across multiple councils.
The fund represents a new approach to AI innovation in public services, connecting academic expertise with real-world operational needs. Projects must demonstrate clear buy-in from at least one local authority partner, be led by a University of Cambridge researcher eligible to hold funding, and deliver results within 12 months.
The initiative builds on ai@cam’s work with local government partners across Cambridgeshire and beyond. Early AI adopters in local government are already demonstrating the technology’s potential in areas like social care, planning consultation analysis, and infrastructure maintenance. This collaboration aims to support councils in identifying promising AI applications and developing appropriate solutions.
How the fund works
Funded projects will receive up to £25,000 for 9-12 months of proof-of-concept development, with ongoing support through monthly community of practice sessions and technical support clinics with ai@cam’s machine learning engineers. A final showcase will document lessons learned and explore pathways for scaling successful solutions across the sector.
Proposals must be submitted by 16.00 on Friday 13 February and should demonstrate clear partnership with at least one local authority.
To apply, we ask for some basic project information, a two page project proposal, and supporting documents to demonstrate local authority support and headline spending plans.
Information session
We will also be hosting an upcoming Q&A information session about the funding scheme on 10:00 - 11:00, Thursday 15 January. You can register for this session here
We encourage all applicants to read the FAQs below before applying. If you have any further questions around eligibility or the application process, please contact Jess Montgomery (jkm40@cam.ac.uk.)
Frequently Asked Questions
The fund provides grants of up to £25,000 to support collaborative research projects between University of Cambridge researchers and local government partners. It aims to develop proof-of-concept AI solutions that address challenges in public service delivery in local authorities.
Applications must be led by a researcher based at the University of Cambridge and demonstrate clear buy-in from at least one local authority partner. We encourage applications that address challenges shared across multiple councils, as these have greater potential for sector-wide impact.
We have already heard from some local authority partners about areas where they would welcome support during a workshop on 24 November 2025. You can read more about these areas on our recent ai@cam blog.
Projects must have engagement with local authority partners throughout development, not just at the application stage. This means ongoing engagement with council staff who understand the operational context and can help ensure the solutions being developed address real needs.
We’re looking for proof-of-concept AI projects that address real-world challenges in local government. The call will not restrict topic areas (but you can read about areas that councils have already flagged as being of interest in our recent ai@cam blog.)
All projects must demonstrate clear public benefit potential. This might include:
- AI tools and applications: AI capabilities to support specific service delivery challenges (for example, document processing, data analysis, prediction models).
- Infrastructure and standards development: Frameworks, protocols, or integration layers that enable AI deployment across fragmented systems. This might include data sharing standards, orchestration platforms, or API specifications that allow different systems to work together.
- Process redesign with AI enablement: Rethinking service delivery processes where AI is one component of a broader improvement. For example, simplifying a complex application process while using AI to support specific steps.
Individual projects can receive up to £25,000 for 6-12 months of proof-of-concept development. Additional support including technical clinics, monthly community of practice sessions, and programme management is provided by ai@cam.
Funded projects must deliver within 12 months of receiving funding. This includes proof-of-concept development, testing with council partners, documentation of lessons learned, and presentation at the final showcase event. The timeline ensures solutions remain relevant to current council needs and maintains momentum for potential scaling.
Proposals will be reviewed to consider their:
- Public benefit potential: Does this address a need that will improve people’s lives? Does the approach align with public expectations from our dialogue work, particularly regarding human oversight, transparency, and accessibility?
- Technical feasibility: Can this be delivered within 9-12 months? Does the team have the right expertise? Are there insurmountable technical or governance barriers?
- Strength of council partnerships: Is there collaboration with committed capacity? Can the team access real operational contexts for testing?
- Delivery capability within 12 months; and
- Potential for scalability across multiple authorities: Could this work for multiple authorities? What would it take to adapt or adopt elsewhere?
- Learning value: Will this generate useful insights even if the AI approach doesn’t work? Does the team have an idea about how to evaluate their impact?
Selection criteria are informed by public dialogues carried out by ai@cam in autumn 2025. You can read more about those dialogues in this ai@cam report.
Beyond financial support, funded projects will receive: monthly community of practice sessions to share progress and lessons learned with other funded teams; technical support clinics offering advice from ai@cam’s machine learning engineers; and focused workshops on shared challenges.
Alongside these project-specific activities, ai@cam will continue to convene networking sessions across councils to support sharing of lessons learned and successful solutions.
We strongly encourage projects to adopt open-source licensing (BSD) to enable sector-wide adoption and sustainable scaling. This ensures that successful solutions can be adapted and implemented by other local authorities without costly licensing barriers, maximising the public benefit of the investment. However, we also understand there may be times when commercial considerations require other approaches.
We strongly encourage applications that address challenges shared across multiple councils. Projects involving multiple authorities should set out how each partner will contribute and benefit.
While the programme builds on ai@cam’s existing relationships with Cambridgeshire councils, applications involving local authorities from other regions are welcome. The key eligibility requirements are active partnership with at least one council and a Cambridge-based researcher who is eligible to hold funding on behalf of the University. Strong applications that address challenges relevant across multiple authorities will be competitive regardless of geographic location.
Applications consist of a Google Form (covering basic team and partner details), a two-page project description, and supporting documents.
Your two-page description should cover:
- The operational challenge you’re addressing and why it matters: What problem are you addressing and why does it matter? Who is affected? Is this challenge shared across multiple authorities?
- Your proposed AI approach and why it’s appropriate: How will you address this challenge? If AI is part of the solution, why is it the right tool for this problem? If you’re developing infrastructure or redesigning processes, how does this enable better outcomes?
- Your council partnership and how you’ll work together: Who is your council partner contact? How will you access real operational contexts for testing? What pathway exists for implementation if successful?
- Your delivery plan and team expertise: What will you deliver in 12 months? Who is on your team and what relevant experience do they bring? What are the key milestones and risks?
- Potential for scaling across multiple authorities: What would it take for other authorities to adopt this?; and
- How you’ll address ethical considerations, including how the project aligns with the concerns expressed in ai@cam’s public dialogues.
You’ll also need to attach: a letter of support from your local authority partner to confirm their willingness to collaborate, and a budget breakdown showing how you’ll use the funding (up to £25,000). We don’t need detailed budgets at this time, but we are looking for headlines on breakdown of spend.
The Google Form requests the following basic project information:
- Project title
- Lead applicant (PI) name, department, email
- Co-investigators (if any)
- Local authority partner(s) name(s)
- Main council contact person(s) and their role/department
- Is this an existing relationship or new partnership?
- Proposed project duration
- Requested funding amount (up to £25,000)
- Proposed start date
- Confirmation that council partner(s) are actively engaged
- Confirmation that the PI is eligible to hold funds in Cambridge
We will be hosting an upcoming information session about the funding scheme from 10:00 - 11:00, Thursday 15 January. You can register for this session here
Applications are now open and you can apply here. The deadline for applications if 16.00, Friday 13 February 2026.
We will be hosting an upcoming information session about the funding scheme from 10:00 - 11:00,Thursday 15 January. You can register for this session here
For more information about the Local Government AI Accelerator, contact Jess Montgomery (jkm40@cam.ac.uk).
Applications are now open and you can apply here. The deadline for applications if 16.00, Friday 13 February 2026.