A Brave New Probation World

Those of us that heard the cobbler delivering the Bill McWilliams lecture in Cambridge recently were struck by two things, his lack of understanding of the probation ethos and his complete awe for everything AI. Well folks, you need to get your head around what he has planned for us, a bright future based on technology and super computers. We all know how good the MoJ track record is with information technology, so what could possibly go wrong?

AI action plan for justice

Published 31 July 2025

Foreword by Lord Timpson

The Prime Minister, the Lord Chancellor, and I are committed to creating a more productive and agile state - one in which AI and technology drive better, faster, and more efficient public services.

That is why I am delighted to introduce the AI Action Plan for Justice - a first-of-its-kind document outlining how we will harness the power of AI to transform the public’s experience, making their interactions with the justice system simpler, faster, and more tailored to their needs.

This plan focuses on three priorities: strengthening our foundations, embedding AI across justice services, and investing in the people who will deliver this transformation. It aligns with the Prime Minister’s vision to build digital and AI capability across government and supports our departmental priority of delivering swift access to justice.

Since joining the Ministry of Justice (MOJ) in July 2024, I have seen real opportunities for AI to improve the working lives of our frontline staff and colleagues - and clear evidence of where it is already making a difference.

I am proud to represent a department that is fundamentally rethinking its use of technology to improve outcomes for the public and contribute to wider economic growth.

I will continue to champion our ambition for the MOJ to lead the way in responsible and impactful AI adoption across government.

This plan marks a crucial first step in delivering that ambition.

James Timpson
Minister for Prisons, Probation and Reducing Reoffending
Lead Ministry of Justice (MOJ) Minister for AI

Executive summary

Artificial Intelligence (AI) has the potential to transform our justice system in England & Wales and deliver our ministerial priorities. AI shows great potential to help deliver swifter, fairer, and more accessible justice for all - reducing court backlogs, increasing prison capacity and improving rehabilitation outcomes as well as victim services. But this opportunity must be seized responsibly, ensuring that public trust, human rights, and the rule of law remain central and AI risks are carefully managed.

This AI Action Plan for Justice sets out the Ministry of Justice’s approach to responsible and proportionate AI adoption across courts, tribunals, prisons, probation and supporting services (referred to here as the justice system). It has been developed in consultation with the independent judiciary and legal services regulators and we will implement it in collaboration with our wider justice sector partners such as the Home Office, the Crown Prosecution Service and our trade unions. It complements wider government efforts to safely modernise public services and builds on the UK’s global strengths in legal services, data science, and AI innovation.

We will focus on three strategic priorities:

1. Strengthen our foundations

We will enhance AI leadership, governance, ethics, data, digital infrastructure and commercial frameworks. A dedicated Justice AI Unit led by our Chief AI Officer will coordinate the delivery of the Plan, with critical input from our Data Science, Digital and Transformation teams. A cross-departmental AI Steering Group provides oversight and an AI and Data Ethics Framework, and communications plan will promote transparency and engagement.

2. Embed AI across the justice system

We will deliver more effective services across citizen-facing, operational and enabling functions alike. By applying a “Scan, Pilot, Scale” approach, we will target high-impact use cases. These include:

• Reducing administrative burden with secure AI productivity tools including search, speech and document processing (e.g. transcription tools that allow probation officers to focus on higher-value work).
• Increasing capacity through better scheduling (e.g. prison capacity).
• Improving access to justice with citizen-facing assistants (e.g. enhancing case handling and service delivery in our call centres).
• Enabling personalised education and rehabilitation (e.g. tailored training for our workforce and offenders).
• Supporting better decisions through predictive and risk-assessment models (e.g. predicting the risk of violence in custody).

3. Invest in our people and partners

We will invest in talent, training and proactive workforce planning to accelerate AI adoption and transform how we work. We will also strengthen our partnerships with legal service providers and regulators to support AI-driven legal innovation and with our criminal justice partners on our collective response to AI-enabled criminality.

We are ready to deliver. AI rollout is already underway with encouraging early results. Initial funding is secured, with additional backing anticipated as we demonstrate impact. As AI technologies mature, we will refine our approach and plan based on real-world outcomes, evaluation, and feedback from staff, trade unions, partners, and the public. We are committed to acting boldly, learning rapidly, and ensuring AI adoption delivers real improvements. Together, these priorities will ensure AI is embedded in our services and transformation programmes, supported by the right foundations, and driven by a productive and agile workforce.

Case study: Using machine learning to create a single offender identity

Having a single, consistent ID for each offender is critical to making better-informed decisions across the justice journey. Fragmented and inconsistent data across different services has made it challenging to track an individual’s journey.

We are building a real-time system linking offender data across agencies to provide a single, consistent view. This tackles longstanding issues with duplication and missing data that can compromise sentencing and rehabilitation.

The system uses Splink, open-source data linking software developed by MOJ data scientists. It applies explainable machine learning to deduplicate records and ensure accuracy. This single view will reduce admin burden, support better decision-making, and enable more advanced AI tools to enhance public safety and rehabilitation outcomes.

2.1.2 Accelerate insight with AI-powered search and knowledge retrieval

Justice system staff often rely on large volumes of unstructured information, including operational procedures, policy documents, case records or legal precedents but traditional search tools struggle to surface what’s most relevant. AI-powered semantic or hybrid search understands meaning, context, and language variation, helping users quickly find the critical information they need.

Unlike standard keyword searches, semantic search understands context, meaning, and relationships between concepts. For example, prison officers could quickly review offender notes to identify risk indicators or rehabilitation opportunities, and caseworkers could swiftly locate relevant guidance or evidence, saving valuable time and improving decision-making.

This ultimately will reduce the time spent manually searching through lengthy documents, so staff can spend more time making informed decisions, and providing better support to those they serve.

As resources allow, we will scale these tools across justice services to reduce inefficiencies, speed up decision-making, and improve frontline service delivery.

Case study: Smarter searches for probation staff

Finding the right information quickly is critical in probation work, yet traditional keyword searches often fall short. Staff were spending time experimenting with different keywords to locate case details, leading to frustrating “search flurries.”

To solve this, MOJ Data Science introduced semantic search in the Probation Digital System (launched June 2025), powered by a Large Language Model (LLM). This AI-driven tool understands context, meaning, and variations in language such as recognising synonyms, misspellings, abbreviations, and acronyms. As a result, staff now receive more relevant results from their very first search, reducing search time and improving decision-making.

This AI-driven improvement reduces search time, enhances decision-making, and allows probation officers to spend more time focusing on offender rehabilitation, risk management, and community safety.

2.1.3 Use speech and translation AI to free frontline staff from admin burdens

Frontline staff spend significant time transcribing meetings and documenting interactions. This is time that could be better spent engaging with people and managing risk. We are piloting AI transcription and summarisation tools in probation services in Kent, Surrey, Sussex, and Wales to reduce this administrative load and improve the quality of recorded interactions.

Case study: Scanning for solutions to support probation officers with notetaking

In probation services, officers dedicate valuable time to writing case notes, which impacts their capacity to focus on rehabilitative work with offenders. High caseloads mean Probation Officers sometimes struggle to find the time to evidence and analyse complex conversations with People on Probation in a sufficiently detailed and consistent format. We are piloting AI-powered transcription and summarisation tools across probation services in Kent, Surrey, Sussex, and Wales.

Early results are very encouraging, with the tool reducing note-taking time by 50% and earning a 4.5/5 satisfaction score from officers. Freed-up time is being used for more meaningful work, better engagement, analysis, and decision-making while improving job satisfaction and reducing stress. In short, the tool is already boosting capacity, service quality, and staff morale.