AI Action Plan Explorer
The Ministry of Justice (MOJ) is at the forefront of responsible AI adoption across government. One year on from publishing the AI Action Plan for Justice, this explorer highlights progress against our ambitions. We are committed to being transparent about how we use AI and will continue to work with industry, academia, civil society and the wider public sector to realise its benefits safely and responsibly.
- Year One snapshot
- to
- Accurate as of
Accelerate insight with AI-powered search and knowledge retrieval
Read the full detail of action 2.1.2 on GOV.UK. (opens in a new tab)
Year 1 progress
In Year 1, significant progress has been made in accelerating insight through AI-powered search and knowledge retrieval. Semantic search capabilities are already live, scaled and delivering value, enabling faster access to relevant information across operational data.
Year 2 priorities
In Year 2, we will focus on progressing AI-powered search and knowledge retrieval tools, expanding use cases, strengthening integration across systems, and using proven models to support insight generation consistently across the justice system.
Case studies (2)
Delius Contact Log Semantic SearchATRS — record published on the Algorithmic Transparency Recording Standard (opens in a new tab)Scale
This AI-powered semantic search tool is helping probation officers find the information they need more quickly and accurately, reducing the time spent searching for guidance and information.
Probation officers work with large volumes of information, including case records and operational guidance. Traditional keyword searches can make it difficult to locate the most relevant information, leading to missed information when authors have used different language and time-consuming “search flurries” to find what they need.
To address this, Justice Digital, Data & Science (JDDS) introduced a semantic search capability within the Probation Digital System. Powered by a Large Language Model (LLM), the tool understands context, language variation and abbreviations, enabling it to return more accurate results from the outset. Unlike basic keyword search, it can interpret synonyms, abbreviations, and misspellings to provide results that match user intent.
This helps practitioners access critical information more efficiently, supporting better risk management and more effective rehabilitation outcomes.
LauriumScale
This AI-enabled software package helps analysts and policymakers unlock insights from unstructured data by extracting structured information from free-text records.
Government services generate large volumes of free-text data through daily interactions with the public. While rich in insight on service effectiveness, emerging needs and operational challenges, this information is often locked in unstructured formats across systems and underused in decision-making.
To address this, Justice Digital, Data & Science (JDDS) developed Laurium through the MOJ's Better Outcomes through Linked Data (BOLD) (opens in a new tab) programme, enabling case notes to be analysed at scale. Since September 2025, Laurium has been rolled out across multiple use cases, including parental imprisonment, Community Sentence Treatment Requirements, children on remand, prison safety, and drug recovery wings - strengthening the frontline evidence base and supporting policy development.
In recognition of its innovation, Laurium won the Analysis in Government Award (Innovative Methods) in January 2026.
Other departments are now adopting Laurium for analytical use cases. We plan to continue expanding use cases and adoption across government.
1. Strengthen Our Foundations
We will strengthen AI leadership, governance and ethics, data and digital infrastructure, and procurement to support AI adoption.
7 actions, 0 case studies: 5 Progressing, 1 Mature, 1 Complete.
2. Embed AI Across the Justice System
We will develop a suite of core AI products to address common, cross-cutting challenges across justice, using a clear “Scan, Pilot, Scale” approach.
12 actions, 13 case studies: 3 Early Stage, 3 Progressing, 5 Mature, 1 Complete.
3. Invest in Our People & Partners
We will invest in talent, training and workforce planning to accelerate AI adoption and transform how we work. We also plan to strengthen our partnerships to support AI-driven legal innovation.
5 actions, 2 case studies: 2 Progressing, 3 Mature.
Actions in 2. Embed AI Across the Justice System
Action 3 of 12- 2.1Mature
Scale AI productivity tools across the system to free up time
1 case study - 2.1.1Complete
Equip every staff member with a secure AI assistant
- 2.1.2Mature
Accelerate insight with AI-powered search and knowledge retrieval
2 case studiesYou are here - 2.1.3Mature
Use speech and translation AI to free frontline staff from admin burdens
3 case studies - 2.1.4Progressing
Automate repetitive admin tasks with AI-powered agents
2 case studies - 2.1.5Mature
Support the use of AI coding assistants to accelerate development and modernise legacy systems
- 2.2Progressing
Explore how AI can improve scheduling and make better use of resources
1 case study - 2.3Early Stage
Explore AI solutions for personalised education and learning
- 2.4Early Stage
Explore how public facing AI assistants could improve access to justice
1 case study - 2.5Early Stage
Improve policy and strategic decision making through AI
- 2.6Mature
Improve decision making through non-generative AI
3 case studies - 2.7Progressing
Evaluate success regularly and adjust our approach as we go
About this snapshot
This explorer will not be updated in real-time. It represents a snapshot of our Year One progress ( to ) against the AI Action Plan for Justice, accurate as of .
In Year One, we committed to establishing strong foundations, building capability and delivering early wins. In Year Two, our priority is to scale what works to improve outcomes more widely across the justice system. All future work will be taken forward in line with appropriate engagement and consultation requirements, including with trade unions where relevant.
