28.09.2026
AI may be dominating the technology conversation, but for police forces looking to turn new technology into better outcomes, the smartest place to start could be somewhere less fashionable: automation.
At the Emergency Tech Show, Andy Wadsworth, Director of Public Sector at Morson Edge, joined Carl Drinkwater, National RPA Programme Director at Lancashire Constabulary, to discuss how robotic process automation (RPA) is already changing policing and why getting those foundations right matters before organisations accelerate towards AI.
The message was clear. AI has huge potential, but technology alone will not deliver the change. Forces need the right processes, clean data, governance and, critically, people who understand and trust the technology.
Automation as the foundation for AI
RPA is hardly the new kid on the technology block. The technology has been available for around two decades and is already being applied to repeatable processes across policing.
For Carl, that maturity is precisely what makes it useful as forces consider the next wave of AI adoption.
Carl Drinkwater, National RPA Programme Director, Lancashire Constabulary: “It’s relatively quick and easy to deploy, relatively cheap to deploy, and it’s safe.”
AI brings a different set of considerations. Testing, governance and confidence in its outputs all need to develop alongside the technology. Rather than racing towards AI without the infrastructure to support it, Carl argues that forces can use automation to establish the processes and methodologies they will need later.
Carl: “For me, it’s absolutely critical you get the foundation right around automation and the AI-supported methodologies which will allow you to transition into AI.”
Andy sees another benefit. RPA gives the workforce experience of technological change in a form that is easier to understand, test and trust.
Andy Wadsworth, Director of Public Sector, Morson Edge: “From a workforce perspective, the human beings have got to go through this change. A dependable piece of software that delivers dependable outcomes means they can trust and see that change. It’s almost like a dress rehearsal for the AI that is going to come to us over the next few years.”
That “dress rehearsal” matters. Successful technology adoption depends on the people expected to work with it every day.
What does RPA in policing actually change?
The national programme already has more than 500 processes on its catalogue for police forces to use, with more than 130 live within Lancashire at the time of the discussion. Applications range from back-office administration and data cleansing to frontline processes with a direct impact on safeguarding.
One example is the Domestic Violence Disclosure Scheme. Processing a request can require information to be researched across several systems, compiled and reported back. Carl explained that the process can take up to 28 days.
RPA can gather that information in minutes.
The gain is bigger than simply saving administrative hours. Faster access to information can support safeguarding decisions sooner, while giving staff more time for work requiring human judgement and interaction.
Data quality is another area where automation is being put to work. Police systems contain large volumes of information, and inaccurate or incomplete records can have operational consequences. Automated processes can continually check and cleanse data, reducing the burden on employees while improving the information available to decision-makers.
That distinction between removing work and improving work runs through the whole conversation.
Andy: “The human that’s involved is able to go and do the thing that requires empathy, judgement and that human-to-human contact, as opposed to always working on systems and occasionally doing the human piece.”
Scaling automation takes more than software
Building an automation in one force is one challenge. Creating something that can work across 43 is another.
Different forces have different systems, processes and local requirements. Carl’s experience of scaling RPA nationally points to three ingredients: repeatable processes, a clear implementation methodology and people who have the authority to make change happen.
A centre of excellence provides part of that structure, bringing together implementation processes, governance and the people required to deliver them. Carl suggests a well-designed RPA process should be capable of moving from start to finish within around two months.
But national expertise cannot replace local knowledge.
Andy: “The adoption needs to happen locally. You can come in and implement those replicable processes, but then the adoption needs to happen locally.”
That means combining technical specialists with subject matter experts who understand the realities of policing, including the exceptions and workarounds that rarely appear neatly on a process map. Experienced technologists with knowledge of national programmes and policing environments add another layer.
Finding those skills is not always straightforward. Developers can be expensive and difficult to recruit, with security clearance adding another consideration. Forces therefore need to think about workforce capability alongside the technology itself.
Productivity means more than cutting headcount
Automation naturally raises questions about jobs. The experience described by Carl and Andy is more nuanced. Rather than simply removing roles, automation can change where human effort is spent.
In areas with persistent vacancies or hard-to-find technical skills, RPA can take repetitive work out of the system. Elsewhere, the same headcount can produce more.
Carl described how automation of the Domestic Violence Disclosure Scheme initially appeared to offer an opportunity to reduce a team of 12 to six. In practice, the organisation retained the team and almost doubled its output, identifying more safeguarding opportunities in the process.
That is an important distinction when measuring productivity. Hours saved are only useful if organisations decide what to do with them.
The return might be reduced overtime or cost. It could be faster service, lower operational risk, better data or greater capacity.
Andy: “We see it changing jobs. We do need people to make decisions based on the data that’s there.”
He adds that when employees can see automation improving services without simply removing jobs, the conversation around adoption changes.
Andy: “It’s getting people to understand that it’s not what it’s taking away, it’s what it’s giving.”
er, safer, and more digitally legible than legacy dockyard roles.
Better data. Faster decisions.
The connection between automation and AI becomes particularly clear when looking at investigations.
Carl used burglary as an example. Researchers can currently need to search several systems, understand the circumstances of an offence, examine known suspects and work through lengthy Police National Database records. The resulting information can run to dozens of pages and take weeks to assemble.
Automation can gather that information. AI could then help summarise a consolidated dataset, allowing officers and staff to move more quickly towards the part humans are there to do: assess, decide and act.
Carl: “If you think how automation can bring that information back, and then you can start to use AI to summarise on a consolidated data set, you can really see the benefits of getting to making decisions and acting on that much more quickly.”
This is where the groundwork becomes important. AI needs more than an algorithm. It needs reliable data, clear processes, governance and controls.
RPA programmes can help forces develop that operating discipline now.
Carl points to established methodologies covering areas such as data protection, ethics, documentation and decision-making. AI will introduce different requirements and stakeholders, but the organisational muscle memory is already being built.
The workforce needs to move with the technology
The future of policing technology will not be decided by technology teams alone.
Change networks, local champions, subject matter experts and clear communication all influence whether new tools become part of everyday operations or remain another piece of technology that never reaches its potential.
Carl has seen attitudes change as employees have become more familiar with automation. Staff who were initially nervous about robots operating across their systems have reached the point of giving them names.
There is a serious lesson behind the humour. Familiarity builds confidence.
AI adoption will require the same attention to people, only at a greater scale. Organisations will need technical specialists who can build and govern new systems, alongside people who understand operational processes and professionals capable of translating technology into better public services.
For Morson Edge, that makes talent part of the productivity equation. Supplying the right specialist skills can help organisations turn technology investment into operational capability, particularly where those skills are scarce, expensive or needed at pace.
Automation provides a practical place to start. It can clean the data, sharpens the processes, builds governance and gives employees experience of working alongside technology. And, done properly, give people more time for the decisions, judgement and human interaction where they make the biggest difference.
