Manchester Prize: Round 2 - Clean Energy Systems

Overview

Overview

The Manchester Prize is a multi-million pound, multi-year challenge prize, launched in 2023 and funded by the Department of Science, Innovation and Technology to reward UK-led breakthroughs in artificial intelligence for public good. Every year for a decade, it is rewarding innovations that will help to transform the lives of people across the UK and continue to secure the UK’s place as a global leader in cutting-edge innovation.

Now in its second year, teams are invited to respond to the following challenge statement.

Challenge Statement

The second Manchester Prize will be awarded to the most innovative and impactful AI solution enabling the UK to accelerate progress towards a net zero energy system. Solutions should demonstrate use of AI that delivers on at least one of the following:

• accelerates the UK’s adoption of clean energy technologies at scale,
• enables efficient or low-cost operations of clean energy systems,
• significantly reduces energy demand, or optimises energy usage.

The winning solution will demonstrate not only technical innovation but also an evidenced road map to near-term (2030) adoption and scale.

Up to 10 of the most promising solutions will each be supported with £100,000 in seed funding, up to £60,000 of compute and additional non-financial support to develop products and services capable of winning the £1 million grand prize in spring 2026.

Who can apply

• Eligible entrants: Entries must come from organisations legally incorporated in the UK (e.g. private limited companies, non-profits, charities, universities). They will not accept applications from individuals or unincorporated groups. See here for guidance on how to incorporate. (Incorporation costs around £50 straightforward applications are normally processed within 24 hours, please check the site to confirm your individual needs.)
• Geographical scope: The lead entrant organisation must be based in the United Kingdom and must be able to receive funds into a UK bank account in the name of the lead entrant. Organisations other than the lead entrant organisation may be based outside of the UK.
• Consortia entries: Teams may enter as a consortium but must nominate one organisation as the lead entrant to submit the application. The lead entrant organisation representing finalist teams will be the organisation that enters into contracts and receives funding from the Manchester Prize.
• Previous Manchester Prize finalists: Finalists from the first Manchester Prize are eligible to participate if submitting a new and original solution, which is distinct from their first Manchester Prize submission.

You must agree to abide by their terms and conditions.

What are they looking for

Example Solutions

Here are some example solutions to further describe the kinds of innovations we might expect to receive – this list is illustrative only and not exhaustive – we expect to receive a range of applications outside of these examples:

• Predicting supply and demand to support smart load management in the grid, allowing for better integration of renewables while minimising transmission constraints.
• Optimising energy consumption in commercial spaces, for example, through (semi-)autonomous control of data centres.
• Maximising renewable energy capture and storage, by leveraging AI to discover new materials and design superior solar panels and wind turbines.
• Ensuring a stable and resilient energy supply, and easing grid stress, by using AI to optimise and coordinate local energy assets, such as heat pumps and batteries.
• Accelerating energy infrastructure projects while minimising environmental and societal impact through AI solutions that support feasibility studies or site plan development.
• Empowering people in their energy transition with solutions that provide AI-powered insights, and tailored interventions and support.

Other considerations

• The end of the Manchester Prize is January 2026. Entrants should consider that they will be expected to have at minimum a working prototype (approximately TRL 6) that can be demonstrated by this point. Finalists who enter to win the grand prize will be asked to quantify and judged on the potential impact of greenhouse gas emissions saved by 2030 and in the longer term.
• Finalists competing for the grand prize will also be required to complete technical validation checks organised by the Manchester Prize team to validate their AI approach.

Assessment areas

The judging criteria for the finalist selection are equally weighted at 20%, meaning they are all judged as equally important.

Innovation: Teams should demonstrate how their solution is an innovation in artificial intelligence (AI), compared to what is the current state of the art. This may be innovation in the underlying AI, a novel application of an existing AI approach, or both. (Innovation in the business model, marketing, or service design is not taken into account – these feature in other judging criteria.)

Impact: Teams should explain how their solution will deliver on at least one of the following:

• accelerate the UK’s transition to clean energy technologies at scale
• enable efficient or low-cost operations of clean energy systems
• significantly reduce energy demand, or optimise energy usage

Teams should indicate the speed and scale at which they expect this impact to be achieved, expected impacts by 2030, and anticipated longer-term impacts. Teams are asked to quantify this impact in expected greenhouse gas emissions saved.

Feasibility: The team should show how their scientific and technical approach is appropriate and how the team has the capacity to deliver a working prototype by January 2026.

Long-term viability: Teams should articulate why there is a credible path to adoption (commercial or non-commercial), and what their plan is to pursue it.

Safety, ethics and sustainability: The team should show they are taking action to showcase best practice in developing and deploying safe and ethical AI, and how they are assessing and mitigating risks to environmental sustainability posed by their solution.