AI in UK Public Services: Smarter Delivery Starts with Smarter Strategy
Consider the potential if the UK public sector were to adopt and implement artificial intelligence at scale and with urgency. The positive impact of AI could be substantial, improving outcomes for the NHS, HMRC, Defence, and other public sector departments. Across these domains, there is a consistent need for increased productivity, cost efficiency, improved decision support, innovation, and error reduction; all areas where AI offers significant benefits.
Recent studies have begun to quantify these advantages. For example, research involving 20,000 civil servants found that AI adoption saved each individual approximately 26 minutes per day, equating to two weeks per year. While this may appear modest, when applied to the nearly 550,000 civil servants in the UK (as of March 2025), the cumulative effect exceeds one million weeks of effort saved annually. This represents a considerable opportunity for efficiency gains across government.
Nevertheless, it is important to proceed with caution. There is a risk of pursuing technological solutions without sufficient strategic alignment—a phenomenon sometimes referred to as “shiny object syndrome.” The enthusiasm for AI must be matched by a clear understanding of its intended purpose and the organisational context in which it will be deployed. Without this, there is a danger of investing in technology that is not fully utilised or understood.
Already, government investment in AI is significant, with over £3.5bn spent to date and a further £2bn allocated this year. In some cases, proper planning is essential - certainly those involved in military outcomes. However, Defence stands just as much to gain as other departments in terms of productivity and there will be much to gain from other government departments and industry. These investments, if properly planned and targeted, could stimulate vast economic growth, creating hundreds of skilled jobs and reinforcing the UK’s prosperity.
Successful transformation is not just about technology—it’s about strategy, delivery, and change. While technology can enable new capabilities, it is the alignment of people and processes that ensures these capabilities are realised. Involving frontline staff, redesigning workflows, selecting the right technology and measuring outcomes holistically are all critical to embedding AI effectively.
Key considerations include:
- Technology must address genuine operational challenges.
- Processes should be redesigned to leverage new capabilities, rather than simply accommodating them.
- People must be adequately trained, trusted, and motivated to engage with new systems.
Lessons from previous initiatives illustrate the importance of this integrated approach:
- In the NHS, diagnostic AI tools were deployed across 66 trusts to accelerate detection of chest conditions. While the technology functioned as intended, misalignment in processes and insufficient engagement with staff led to slow integration and limited adoption.
- At the Department for Work and Pensions, promising prototypes such as A-cubed (for job coaches) and Aigent (for disability benefit claims) were discontinued due to unprepared processes and a lack of staff readiness to trust the tools.
- Earlier, a fraud-detection algorithm incorrectly flagged approximately 200,000 legitimate housing benefit claims, highlighting failures in process design and the need for human oversight.
These examples reinforce a consistent lesson: successful transformation requires the coordinated advancement of people, process, and technology.
To sustain progress, the following principles should be observed:
- Prioritise people: Involve frontline personnel early in the design and implementation of AI solutions. Their insights are critical to ensuring that technology is fit for purpose.
- Redesign processes: Legacy workflows should be re-evaluated and adapted to ensure that AI tools simplify tasks rather than introduce additional complexity.
- Select technology judiciously: There are many AI tools beyond LLM chatbots, so it is important to follow a selection process and identify the actual requirements.
- Measure outcomes holistically: Success should be assessed not by the number of pilot projects, but by tangible improvements in efficiency, error reduction, and the experience of citizens and staff. Metrics should reflect the balanced contribution of people, process, and technology.
In Defence and across the public sector, a strategic and measured approach to AI adoption will be essential to realise its full potential. Leaders must move beyond technology-first thinking and invest in the people and processes that underpin successful transformation. By embedding AI within a robust strategic framework, the UK can become a leader in AI while improving the lives of the British people.
Author
Darter
Darter
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Kir Nuthi
Kir Nuthi
Kir Nuthi is the Head of AI and Data at techUK.
She holds over seven years of Government Affairs and Tech Policy experience in the US and UK. Kir previously headed up the regulatory portfolio at a UK advocacy group for tech startups and held various public affairs in US tech policy. All involved policy research and campaigns on competition, artificial intelligence, access to data, and pro-innovation regulation.
Kir has an MSc in International Public Policy from University College London and a BA in both Political Science (International Relations) and Economics from the University of California San Diego.
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Usman Ikhlaq
Usman joined techUK in January 2024 as Programme Manager for Artificial Intelligence.
He leads techUK’s AI Adoption programme, supporting members of all sizes and sectors in adopting AI at scale. His work involves identifying barriers to adoption, exploring solutions, and helping to unlock AI’s transformative potential, particularly its benefits for people, the economy, society, and the planet. He is also committed to advancing the UK’s AI sector and ensuring the UK remains a global leader in AI by working closely with techUK members, the UK Government, regulators, and devolved and local authorities.
Since joining techUK, Usman has delivered a regular drumbeat of activity to engage members and advance techUK's AI programme. This has included two campaign weeks, the creation of the AI Adoption Hub (now the AI Hub), the AI Leader's Event Series, the Putting AI into Action webinar series and the Industrial AI sprint campaign.
Before joining techUK, Usman worked as a policy, regulatory and government/public affairs professional in the advertising sector. He has also worked in sales, marketing, and FinTech.
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Sue Daley OBE
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In 2025, Sue was honoured with an Order of the British Empire (OBE) for services to the Technology Industry in the New Year Honours List.
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A key influencer in driving forward the data agenda in the UK, Sue was co-chair of the UK government's National Data Strategy Forum until July 2024. As well as being recognised in the UK's Big Data 100 and the Global Top 100 Data Visionaries for 2020 Sue has also been shortlisted for the Milton Keynes Women Leaders Awards and was a judge for the Loebner Prize in AI. In addition to being a regular industry speaker on issues including AI ethics, data protection and cyber security, Sue was recently a judge for the UK Tech 50 and is a regular judge of the annual UK Cloud Awards.
Prior to joining techUK in January 2015 Sue was responsible for Symantec's Government Relations in the UK and Ireland. She has spoken at events including the UK-China Internet Forum in Beijing, UN IGF and European RSA on issues ranging from data usage and privacy, cloud computing and online child safety. Before joining Symantec, Sue was senior policy advisor at the Confederation of British Industry (CBI). Sue has an BA degree on History and American Studies from Leeds University and a Masters Degree on International Relations and Diplomacy from the University of Birmingham. Sue is a keen sportswoman and in 2016 achieved a lifelong ambition to swim the English Channel.
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