In summary:
- The UK’s Police Reforms White Paper and Police.AI mark the biggest shift in policing, driving a nationally coordinated, tech‑enabled model.
- AI adoption will transform productivity, investigations and crime prevention, but success depends on data quality, interoperability and rigorous ethical oversight.
- Industry must collaborate with policing on shared standards, proven operational value and national‑scale solutions to deliver trusted, responsible AI across all forces.
The AI choices our police industry makes in the next 24 months will determine whether the next decade will be one of empowerment or passive observation. The Home Office’s Police Reforms White Paper, From Local to National: A New Model for Policing, represents the most significant change to policing in England and Wales for over two centuries. Announced by Home Secretary Shabana Mahmood, it sets out a wide-ranging reform programme designed to create a police service that is both more locally rooted and more nationally coordinated.
Key proposals include reviewing force mergers, creating a National Police Service to tackle serious and complex crime, strengthening national accountability and standards, and modernising the workforce by attracting specialist skills such as cybersecurity and technology expertise. The reforms also emphasise consistent neighbourhood policing, improved public order responses, and better support for officer wellbeing.
Technology sits at the centre of this transformation, reflecting a clear recognition that policing must modernise its capabilities to keep pace with criminality and meet rising public expectations.
Policing and technology – a system catching up
Policing has historically been playing catch-up in how it adopts and uses technology.
The 2025 Cityforum Digital Policing Summit Report, highlights the scale of the issue: although forces invest around £2 billion a year in technology, 97% of that spend goes toward maintaining legacy systems rather than driving innovation. So, while innovation has taken place across forces, progress has often been fragmented, inconsistent, and constrained by legacy systems and siloed data.
The National Police Chiefs' Council (NPCC) has set a clear direction through its
AI Strategy and
AI Covenant, alongside the development of the Police.AI and associated plans for a national AI lab. The White Paper reinforces this ambition through significant investment and a stronger emphasis on collaboration with academia and the technology sector.
This signals a shift in how policing expects to work with industry, moving beyond isolated technology deployments towards long-term capability development, shared standards, and responsible innovation at national scale.
Police.AI: a national centre for AI in policing
Among the White Paper’s most significant initiatives is the creation of
Police.AI, a national centre to accelerate the responsible adoption of artificial intelligence across all 43 forces in England and Wales. Backed by over £115 million of funding over three years, and forming part of a wider £140 million investment in policing technology, Police.AI will identify, test and scale AI tools that deliver measurable operational outcomes, as well as providing strategic coordination and best practice guidance to enable it.
The Home Office estimates the programme could return up to six million hours to frontline policing annually – the equivalent to 3,000 officers – by reducing administrative burdens, accelerating investigations, and improving the experience of victims and witnesses.
The centre aims to address the current fragmentation of innovation across forces. While individual organisations have trialled technologies such as facial recognition, call transcription and deepfake detection, adoption remains inconsistent. Police.AI provides a mechanism to standardise evaluation, apply rigorous scientific testing, and deploy proven tools nationally.
Transparency and trust are central to this model. A public registry of AI tools, robust evaluation and bias testing, and clear governance frameworks will support ethical deployment. Early priorities are expected to include disclosure processes, CCTV analysis, case file production, crime recording, and translation services.
Where AI can transform policing outcomes
The NPCC’s strategy identifies three priority areas where AI should support policing:
improving productivity and efficiency.
tackling crime and harm.
countering the criminal threat.
These priorities translate into a wide range of operational applications, including robotic process automation, disclosure processes, CCTV and body-worn video analysis, criminal justice workflow automation, facial recognition, AI-supported control room operations, and tools to identify offenders involved in serious violence and sexual crimes. One specific focus of this is how AI could be used to accelerate the government's pledge to
reduce violence against women and girls by 50% over the next 10 years. Alongside this, AI is also being explored to detect deepfakes, protect vulnerable individuals, and identify those presenting the greatest risk.
The combination of using AI to respond to crime and prevent it creates opportunities for industry to help policing stay ahead of evolving threats – strengthening prevention, designing out crime, and shaping future operational capability.
Technology partners can support existing initiatives such as Clare’s Law disclosures, continuous vetting and identity resolution within the Disclosure and Barring Service, and AI-assisted risk assessment with human oversight. Emerging areas of interest include virtual reality training, financial and cyber forensics, intelligent call triage, multi-agency data sharing for missing person investigations, and automated audit tools for supervisory oversight.
These areas reflect real operational challenges and demonstrate how AI could support both preventative and reactive policing models.
Delivering the White Paper’s ambitions: an industry call to action
No single organisation can solve these challenges. We need shared standards, shared learning and shared accountability across government, private sector and civil society. Programmes of this magnitude do not happen without significant effort and a clear understanding of both policing realities and public expectations. From the outset, close collaboration between policing and industry has driven this work. We’ve had the privilege to consult on how this initiative has been shaped, so we’ve seen how many of the long-term outcomes depend on decisions being made today and why getting the foundations right will determine whether Police.AI delivers lasting impact.
The direction set out in the White Paper – alongside the NPCC’s strategy – creates a clear mandate for how industry must respond. Delivering Police.AI’s ambitions will require technology suppliers to work differently: collaborating more deeply with policing, prioritising operational outcomes, and building solutions that scale nationally.
From our work across the sector, we see several priorities that should guide industry’s response:
Fix the data, or the AI won’t work
AI can’t deliver meaningful results when it’s built on messy, inconsistent or isolated data. If the data is weak, or worse, bias, trust will be weak especially among officers using the tools and the public affected by their decisions. High-quality, interoperable data is what builds confidence, enables ethical decision-making, and reduces risk. Industry has a critical role to play here, focusing first on robust, open data plumbing rather than jumping straight to “cutting-edge” tools.
Start with shared data standards and common definitions before deploying AI tools.
Invest in data quality, lineage, and auditability as core infrastructure.
Prioritise interoperability between systems so AI can operate seamlessly across forces.
Prove value in the field
Credibility beats promises. The fastest way to build momentum is by demonstrating real, measurable efficiencies in live policing environments – for example in redaction, transcription or case file preparation. Measure the impact, publish the results, and repeat. Showing what works today is far more powerful than talking about what might work tomorrow.
Focus first on high-volume, low-discretion tasks where results can be measured quickly.
Agree success metrics upfront (time saved, error reduction, officer satisfaction).
Publish results openly and iterate based on evidence, rather than scaling unproven tools.
Trust is the product
In policing, trust is not a nice-to-have – it is the product. Radical transparency is essential to rebuilding and maintaining legitimacy. If the public cannot see the safeguards, or officers cannot rely on tools that have been rigorously tested for bias, accuracy and explainability, the technology will fail. Police.AI’s emphasis on standards, registries, audits and oversight is not bureaucracy; it is what makes responsible AI adoption possible at scale.
Make bias testing, model performance, and limitations accessible to all stakeholders.
Use model cards, audit trails, and clear escalation routes as standard practice.
Communicate openly with the public about AI use, safeguards, and operational decisions.
Design with officers, not for them
Policing is complex, high-pressure and unpredictable. Tools that look good in a lab but do not fit frontline reality will not be used. Co-designing with officers matters: simple user experiences, role-based training, and human-in-the-loop by default all help build confidence. When officers understand and can explain how a tool works, they are better equipped to deliver outcomes the public can accept.
Involve frontline officers early and continuously in design and testing.
Default to human-in-the-loop workflows with clear override and escalation paths.
Provide role-based training so officers understand not just how a tool works, but when and why to use it.
Think national-first
With a more centralised future market, industry needs to design for national scale from the outset. That means open standards, interoperability, and alignment with central assurance frameworks. It also means shifting from selling standalone software to becoming long-term partners in capability – helping to build a national ecosystem that prioritises fairness, safety and efficiency.
Build software and tooling that can be configured locally without fragmenting nationally.
Align solutions with central assurance frameworks from day one.
Position yourself as a long-term partner in capability development, not just a vendor of software.
Understanding the real challenges policing faces
Technology must deliver genuine improvements to frontline policing and outcomes for victims, witnesses and communities. Solutions must be operationally relevant, rigorously tested, ethically sound, and demonstrably effective.
Achieving this requires deep understanding of the policing environment and close partnership between industry and law enforcement – focused not simply on innovation, but on measurable performance improvement and public value.
A pivotal moment for policing leadership
Police.AI represents a pivotal moment for technology in policing. If delivered well, it has the potential not only to modernise policing operations, but to reset how innovation, ethics and public trust are balanced in one of the most sensitive areas of the public sector.
If Police.AI is a pivotal moment for technology in policing, it is also a pivotal moment for leadership.
Public sector leaders do not need to become technologists, but they do need to become AI-literate: able to interrogate systems, understand risk, ask better questions, and balance innovation with accountability.
That is precisely why we invested in building AI for Leaders - to give free access to training that equip decision-makers with the clarity and confidence to govern AI responsibly.
If you’re navigating AI adoption in complex, high-trust environments, now is the time to build that capability: AI for Leaders.