Gareth Mapp is Managing Director of Warp Technologies, a Brighton-based company that specialises in helping businesses make sense of their data, streamline operations, enhance decision-making and drive measurable growth.
To find out more, see Warp Technologies.
Much like other regions and conversations globally, artificial intelligence is dominating the headlines in the UK – so much so that the government recently announced the launch of its AI opportunities action plan. AI has already made its way into daily operations and is reshaping how the public interacts and engages with public services.
Photo by Soliman Cifuentes / Unsplash
This isn’t just about automation; it’s about reimagining public service delivery and meeting the needs of citizens while facing cuts to budgets and resources. We’ve seen how the NHS is implementing AI for diagnostic support and patient flow. Local authorities are using predictive analytics to better allocate limited resources and make repairs to potholes and rectify issues in social housing.
So, what are the key trends on the horizon for business leaders and the active considerations that need to be mulled over when it comes to AI development?
The rise of agentic AI
In past 12 months, we’ve seen a massive shift for businesses using artificial intelligence with the rise of agentic AI. We’ve moved from a foundational level of AI that guides you like a GPS to an advanced layer operating like a self-driving car that doesn’t just give you recommendations, it intrinsically acts on your behalf and makes decisions in real time.
While the above is likely to fill many public sector and local government leaders with fear at the thought of technology making a decision without human intervention, there are a plethora of examples of how agentic AI can strike the balance of successfully operating in sensitive situations while maintaining appropriate human oversight to improve delivery of services to the public. However, while proactive AI is very good at detecting anomalies across services, ensuring it is outcome based is a whole other challenge. This depends heavily on the quality of training the data, the integration of human intelligence via models such as human-in-the-loop (HITL) and the operational context in which it is delivered.
There are a range of risks that government leaders need to be aware of, from algorithmic bias that could worsen existing inequalities in public services to challenges with accountability gaps where decisions are made by systems rather than people. There can also be an over-reliance on automation, which can erode human judgement or resilience in critical services. Despite the key advances of using this technology, there are also limits – which shows how AI is not replacing humans across the sector but more so augmenting operations to bring greater efficiency gains.
Multimodal AI: a frontier for frontline teams
The utilisation of multimodal AI is unlocking substantial business growth for organisations across local government. The use of multimodal AI systems is enabling organisations to process, interpret and generate a range of content across multiple types of data such as text, images, audio and video. Having the capability to process multiple data sources is proving game changing for specific sectors. Emergency services, healthcare and many other sectors are also benefiting from this advancement. This AI input coupled with medical imagery capture by utilising X-rays and MRIs is advancing the way diagnostic support is delivered. Patient records, notes and doctor’s assessment criteria can be run in parallel alongside each other to provide patient care information in one view.
Across emergency services where there are often multiple forms of data, be it CCTV footage, call audio and video, and text reports, multimodal AI is bringing all this data together in one convenient place. This is helping to reduce incident times and analyse data much faster by removing manual processes.
Data access and governance
Recently, there’s been a seismic shift from pure AI excitement to AI delivering tangible benefit. We’re seeing real-world examples of successful use cases and improvements to business operations, from automating processes and freeing up hundreds of hours for front line workers, to drastically reducing waiting times across public services.
Considering the many benefits that come with leveraging AI solutions, organisations also need to be aware of the ethical implications and the key governance considerations. These need to form a crucial part of go-to market strategies and also act as a guidance framework for employees. Organisations would benefit by adopting transparency standards and algorithmic impact assessments, as well as employing processes such as redress mechanisms which are essential for displaying accountability and fairness in the delivery of public services. Ultimately, data breeds data and one of the common pitfalls of using AI is failing to register that data collection and retention will take place. Entering sensitive information or giving AI access to private data could ultimately give the green light for this material to be available publicly, causing implications to the wider business or individual it relates to. An essential pillar to this is building trust with the public and recognising that citizens may not want their data being analysed and collected, making transparency, accountability and consent in system design essential.
One of the most pressing issues in the AI landscape today is the absence of comprehensive legislation. While the EU, for example, is progressing with frameworks like the AI Act, the UK’s approach remains more fragmented, relying on existing regulatory bodies rather than a single statutory framework. This creates ambiguity around standards, responsibilities and redress mechanisms; particularly concerning when AI is deployed in critical public services. Public sector and local government leaders are navigating powerful technologies without a clear legislative compass, increasing the risk of inconsistent practices, leaving room for misuse or unintended harm.
As the UK accelerates its AI journey across public services, public sector leaders must move from passive exploration to strategic execution. That means investing not only in the right tools, but in the right frameworks, embedding transparency, accountability, and citizen trust into every AI deployment. Those who act decisively now won’t just drive efficiency; they’ll redefine the very fabric of public service delivery for the digital age. My advice: start small, think big and move fast, or risk missing out on the huge potential that successful AI adoption offers.
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