AI in policing: safeguards can't keep up, new research warns

Artificial intelligence is being adopted across policing and the wider criminal justice system of England and Wales faster than the rules designed to govern it, according to major new research published by Northumbria University.

The study - the most comprehensive mapping exercise of its kind to date - identifies 70 AI tools already deployed, trialled, or under development across the criminal justice system, from contact-centre triage and witness statement drafting to digital forensics and facial recognition.

Led by Northumbria University in partnership with the Universities of Glasgow, Northampton, Leicester, Newcastle, and Cambridge, the four-year PROBabLE Futures project was funded by Responsible AI UK as a £4.2 million Keystone Project. The team spent the past year building an interactive mapping tool and conducting interviews between May 2025 and January 2026 with police officers, government officials, legal professionals, oversight bodies, academics, and technology vendors.

Of the 70 tools identified, 27 are already live, with around 34 at trial or pilot stage. More than half (52%) come from commercial vendors, with most activity concentrated at the community policing, intelligence, and investigation stages of the criminal process.

The research delivers a clear central finding: AI is already generating real value in transcription, redaction, crime analysis, vulnerability identification, and officer welfare - but only where it has been carefully designed, matched to clearly defined operational problems, and robustly evaluated. Across the wider system, adoption is outpacing the institutional, evidential, and governance frameworks needed to support it.

A particular focus of the report is the concept of the 'human in the loop' - the principle that a person should review and remain accountable for AI outputs. The research finds this principle often exists in name only, providing a false sense of assurance rather than a genuine safeguard.

The report also highlights a counterintuitive risk: as a tool approaches near-perfect accuracy, people may stop checking its outputs - meaning rare errors are more likely to go undetected and carry serious consequences. This danger grows when AI systems are linked together in sequence, with each stage potentially inheriting and compounding errors introduced earlier.

Lead author Dr Temitope Lawal, Research Fellow in Law at Northumbria University, said: “Our starting point was a simple question: what AI systems are actually being used across the criminal justice system? Despite growing interest in AI, there was surprisingly no single place where this information could be found. This project provides the first systematic attempt to map that landscape. We hope the interactive mapping tool and the accompanying report will become a resource for policymakers, practitioners, researchers, journalists, and members of the public who want a clearer understanding of how AI is reshaping criminal justice in England and Wales.”

The report sets out 26 recommendations directed at the Home Office, PoliceAI, the College of Policing, the Crown Prosecution Service, the judiciary, technology providers, and the research community. These include independent national evaluation of AI tools beyond facial recognition, mandatory transparency and public registries, stronger procurement and testing standards, better workforce training, and new research into the chaining of AI systems.

The findings come at a moment of significant national attention on AI governance, with the recent establishment of PoliceAI and the Home Office white paper From Local to National: A New Model for Policingboth highlighting the urgent need for greater transparency and coordination in AI deployment.

The report and interactive mapping tool are available online.