Review of AI deployment in the electricity networks: terms of reference

The government has asked, Lucy Yu, the AI Champion for Clean Energy, to carry out a review of AI deployment in the electricity grids. This document sets out the terms of reference for the review. It includes: * purpose and objectives * scope * leadership and governance * methodology * timelines We will publish the final report by Summer 2026. --- ## 1. Background As the electricity system becomes more complex and weather dependent, new challenges arise for grid planning, operations, and management, including in relation to forecasting, optimisation, and flexibility. Methods and approaches that are used today will need to adapt and evolve for the future, along with the infrastructure, systems, and institutions that support them. Data and Artificial Intelligence (AI) technologies offer transformative potential to address such challenges; whether supporting and enhancing today’s practices, or unlocking radical new approaches, such as the prospect of autonomous grids enabled by advanced AI technologies. However, deployment remains fragmented due to: * limited evidence * gaps in regulation * barriers to accessing data * immature simulation and testing landscape for tools, which are essential for verification and validation With the right focus, AI could play a pivotal role in delivering each of the government’s five Missions, including that to ‘[Make Britain a clean energy superpower](https://www.gov.uk/missions/clean-energy)’. Therefore, we area setting up a review that will be led by the government appointed AI Champion for Clean Energy. It will provide an expert assessment of the opportunities, risks, and enablers for AI technologies in grid planning and management, helping government, regulators, and industry align efforts to accelerate innovation safely and effectively. This will be through the lenses of technology development, real world use cases, system safety and the classification of risk. The Review forms part of wider government work on AI and decarbonisation, including delivery of the Clean Power 2030 and Clean Energy Superpower Missions, and supports the ambitions set out in the AI Opportunities Action Plan. ## 2. Purpose and objectives The primary objectives of the review are to: 1. Map current and emerging AI technology applications across electricity infrastructure, grid planning, operations, and management. This will focus on those with the highest potential impact for the UK’s energy system, future R&D requirements and consider the development of exportable technologies. 2. Identify barriers and enablers to AI deployment, including technical, legal, regulatory, and data-related challenges including what data is required and where access to data is an issue. 3. Assess the potential system benefits of AI including for affordability, energy security, flexibility, and decarbonisation, and the potential risks and challenges that could undermine delivery of these benefits. 4. Provide recommendations to government, regulators, and industry on rapid, safe and effective deployment pathways of AI technologies across the grid, including future advanced AI technologies. ## 3. Scope The Review will cover applications of AI for: * grid connection, planning, operation, balancing, stability services, grid flexibility (including domestic and industrial/commercial-led flexibility) and optimisation * transmission and distribution-level applications * relevant enabling conditions such as data access, interoperability standards, quality assurance, digital testing and simulation environments, and supporting infrastructure. * the regulatory and governance landscape (for example, Ofgem, NESO, DESNZ, and DSIT responsibilities) * how to build public trust and confidence to support technology adoption and policy development Out of scope: * endorsement of specific AI products or suppliers * siting of data centres or their energy usage * detailed assessment of cybersecurity policy (though interfaces with AI deployment may be noted) ## 4. Leadership and governance The Review will be independently led by Lucy Yu, the DESNZ-appointed AI Champion for Clean Energy. Technical support will be provided by ADViCE[[footnote 1]](#fn:1), with engagement from government. ## 5. Methodology The Review will adopt a mixed-evidence approach, including: * desk-based literature review and analysis of existing government, industry, and research activities; this will include and build on the work already undertaken by ADViCE * targeted engagement with academics, industry, trade associations, and other interested parties through roundtables, workshops, and bilateral meetings; this will feed into analysis and test emerging findings * synthesis of case studies and international best practice ## 6. Deliverables and timelines The Review will produce a report by Summer 2026 with clear, actionable recommendations. The government will respond to the recommendations in the review within 3 months of the review concluding. This programme does not place any obligation on government to follow through on these recommendations, and any decision to pursue these will be subject to due diligence, including consideration of costs, benefits and careful consideration of the risks associated with AI. ## 7. Confidentiality and publication All information gathered during the Review will be treated in accordance with government security and data-handling policies. The final report will be published on GOV.UK. ## 8. Contact For enquiries to this review, please contact ADViCE@turing.ac.uk. 1. ADViCE stands for AI for Decarbonisation’s Virtual Centre of Excellence. It is funded by DESNZ and is delivered by a consortium comprising Digital Catapult, Energy Systems Catapult, and The Alan Turing Institute. [↩](#fnref:1)