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By Paul Miller, VP of Sales, Northwest Europe, Penlink
AI in policing has moved from pilot projects into everyday conversations across intelligence analysis teams. Forces across the UK and Europe face rising volumes of digital material, stretched resources and growing public expectations. Generative AI promises help with all three.
Yet the question facing police leaders is not whether to use these tools. It is how to use them in ways that stand up to scrutiny in court, in oversight and in public. The answer starts with a simple principle. AI supports the analyst, and the analyst remains accountable.
Every serious investigation now generates more material than a team can read line by line, and the investigative platforms behind that work hold more each year. Phone downloads, open-source content, financial records and communications data all arrive in volume. As a result, analysts spend much of their time sorting rather than thinking.
Generative AI can carry part of that load, which is why AI in policing has gathered such momentum. It can summarise long documents, translate foreign-language material, surface recurring names and draft first versions of routine reports. Therefore, skilled people gain time for assessment, hypothesis and decision.
This is the force multiplier argument. AI does not add officers to the establishment. It does, however, return time to the officers and staff already in post, and lets data analytics keep pace with the caseload.
UK policing has moved quickly to set expectations. Chief constables have signed the National Police Chiefs’ Council Covenant for Using AI in Policing. It commits forces to transparent, responsible and accountable use. Under the Covenant, AI outputs should not simply be accepted without human scrutiny.
The College of Policing has published practical guidance on selecting, testing and embedding AI tools. A national AI playbook and a responsible AI checklist sit alongside it. Additionally, government has committed £115 million to help policing adopt AI safely, and a public register of AI deployments is in development.
Underneath sits the law that already governs police data. Part 3 of the Data Protection Act 2018 sets the rules for processing personal data for law enforcement purposes. Furthermore, any output that informs a case must still meet the evidential and disclosure standards of the courts.
Across the European Union, the AI Act sets the most detailed rulebook yet. It classes many law enforcement uses of AI as high-risk, bringing requirements for risk management, data quality, documentation, accuracy and human oversight. Some practices, such as most real-time remote biometric identification in public spaces, are prohibited outside narrow exceptions.
The timeline has shifted, though. The Digital Omnibus amendment came into force in July 2026. It moved the main high-risk obligations for law enforcement and other standalone systems from August 2026 to December 2027. However, the prohibitions already apply, and transparency obligations remain on their original schedule.
European police services also work within the Law Enforcement Directive, which governs how personal data is processed for policing purposes. The UK sits outside the AI Act. Even so, AI in policing on both sides of the Channel points in the same direction: human oversight, documented decisions and proportionate use. For teams that cooperate across the Channel, that shared direction makes joint work easier to defend.
Generative AI is fluent, and fluency is not the same as accuracy. Models can misread context, miss nuance in slang or coded language and occasionally produce confident errors. Consequently, any output that matters needs a trained person to check it against the source material.
Some decisions should always sit with people. Assessing credibility, weighing proportionality, deciding on intrusion and judging risk to the public all require accountable human judgement. AI can inform those decisions. It cannot own them.
Transparency matters as much as accuracy. Analysts need to trace each point in a summary back to the underlying material. Forces, in turn, need records of how AI was used. Those records let decisions be explained to a court, an oversight body or the public.
Used this way, AI in policing becomes a genuine colleague. It handles volume, speeds up first drafts and points to what deserves attention. The analyst brings experience, context and accountability.
AI can read faster than any analyst. Only the analyst can decide what it means.
See how CoAnalyst360 supports analysts in a live investigation. Join our free webinar, Illegal Immigration and Poly Criminality: Investigating an Albanian Organised Crime Group, on 10 November 2026 at 1:00 pm GMT. Open to government and law enforcement personnel. Register now.
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