The UK public sector doesnt have an AI problem, it has an orchestration problem

Date:
Wed, 27 May 2026 09:30:03 +0000

Description:
The UK public sector doesnt have an AI problem, it has an orchestration problem

FULL STORY ======================================================================Copy link Facebook X Whatsapp Reddit Pinterest Flipboard Threads Email Share this article 0 Join the conversation Follow us Add us as a preferred source on Google Newsletter Subscribe to our newsletter The UK public sector is accelerating its adoption of artificial intelligence , but without a clear sense of what that acceleration is meant to achieve. A recent Institute for Public Policy Research (IPPR) report warns that the government risks focusing on speeding up AI deployment without defining how it will improve peoples lives. Peter Corpe Social Links Navigation

Industry Leader for the UK Public Sector at Appian. The UK public sector is not short on AI ambition. From central government to local authorities and
the NHS, organizations are investing heavily, launching pilots, and signaling intent to transform services with artificial intelligence. And yet, delivery continues to lag behind expectation. That gap between activity and outcomes
is already visible inside government. New research helps to explain why. Nearly half (45%) of public sector AI initiatives are still being deployed as bolt-ons or standalone tools, rather than embedded into the workflows that
run services. Latest Videos From You may like UK councils are betting big on AI, but complexity could swallow the returns Enterprises dont have an AI problem, they have a data problem Everyones doing AI, but whos seeing value?

This is not just a technical detail. It is the root of the problem - because when AI sits outside the process, it cannot transform the process. Activity isnt progress There is a growing disconnect in the public sector between AI activity versus AI outcomes.

On paper, adoption looks healthy. Public sector workers report multiple services using AI tools , and leadership optimism is high. But scratch
beneath the surface and a different picture emerges: only 29% say their organization is delivering on most of its AI commitments, while many report a clear gap between strategy and execution.

This is not a failure of technology. It is a failure of how that technology
is being applied. Too many organizations are mistaking experimentation for transformation. Bolt-on AI makes it easy to show progress, but it does not always deliver it. Are you a pro? Subscribe to our newsletter Sign up to the TechRadar Pro newsletter to get all the top news, opinion, features and guidance your business needs to succeed! Contact me with news and offers from other Future brands Receive email from us on behalf of our trusted partners
or sponsors By submitting your information you agree to the Terms &
Conditions and Privacy Policy and are aged 16 or over. The bolt-on trap The appeal of bolt-on AI is obvious. It is fast to deploy, low-risk, and highly visible internally. Whether it is a chatbot , a co-pilot, or a standalone analytics tool, it allows teams to do something with AI without disrupting existing systems.

But that is precisely the problem. When AI is layered onto existing processes - rather than designed into them - it inherits all the inefficiencies, fragmentation, and constraints of those processes. It may improve individual productivity , but it does not improve the organizational system as a whole.

In practice, this leads to familiar outcomes: disconnected tools, duplicated effort, limited auditability, and minimal impact on citizen-facing services. What to read next Why Agentic AI demands business process re-engineering Why
a staggering 42% of business AI projects are currently failing Why health AI needs a new approach, not just smarter algorithms

It also helps explain another striking finding: 75% of UK citizens cannot
name a single way the public sector is using AI today. AI is being deployed, the impact just isnt being felt or communicated properly yet. Why process matters The missing piece is orchestration. AI does not deliver value in isolation. It delivers value when it is embedded within a defined organizational process - where it has a clear role, access to the right data, and a direct influence on the outcomes.

In an integrated process, AI is not an add-on. It is part of how work gets done. Every decision feeds into an action. Every action is tracked and audited.

Every outcome can be measured and improved. Crucially, this also creates the guardrails that public sector organizations need to ensure transparency, accountability, and compliance are built in from the start.

This is particularly important in government, where trust is fragile and scrutiny is high. Citizens are not just asking whether AI works; they are asking whether it is fair, secure, and accountable.

Those questions cannot be answered by standalone tools. They can only be answered by systems that are designed end-to-end. Fix the process, then apply the intelligence Encouragingly, there is growing recognition of this within the sector. The majority of both public sector workers and citizens agree
that existing processes must be fixed before new AI technologies are introduced.

This is exactly the right instinct. Because AI is not a shortcut around
broken processes. It amplifies whatever it is given. If the underlying workflow is inefficient or fragmented, AI will scale those problems rather than solve them.

But if the process is well-designed, structured, connected, and measurable, then AI can unlock significant gains in speed, accuracy, and service quality.

The challenge is that process transformation is harder than tool deployment. It requires organizations to rethink how work flows across systems, teams,
and departments. It requires coordination, not just capability - in short, it requires orchestration. From pilots to public impact As the IPPR argues in
its report, acceleration alone is not a strategy. The real challenge is direction - ensuring AI is applied in ways that deliver clear public value.

The next phase of public sector AI adoption will not be defined by new models or new tools. It will be defined by how effectively organizations embed AI into the processes that matter most.

That means moving beyond isolated use cases and towards integrated systems.
It means designing AI into processes from the outset, rather than adding on afterwards. And it means measuring success not by internal efficiency alone, but by outcomes that citizens can see and experience.

Theres no ambiguity around whether public bodies are adopting AI. What we
need to ask now is whether they are considering the bigger picture when implementing AI. Until that is addressed, AI will continue to deliver pockets of value but fall short of the systemic transformation that has been
promised. We've featured the best IT automation software. This article was produced as part of TechRadar Pro Perspectives , our channel to feature the best and brightest minds in the technology industry today.

The views expressed here are those of the author and are not necessarily those of TechRadarPro or Future plc. If you are interested in contributing find out more here: https://www.techradar.com/pro/perspectives-how-to-submit



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