Bridging the real digital gap in the public sector

Across the UK and beyond, public sector organizations have made major strides toward digital transformation.

From online tax portals to digital health records, citizens are expecting the same seamless, data-driven experience they receive from private sector services, and these expectations are increasingly being met.

But there’s still a persistent digital gap between aspiration and execution. Many government departments remain constrained by legacy technology, fragmented systems, and organizational silos that make joined-up service delivery a lot harder to achieve.

Even where new platforms exist, human and process barriers, such as skills gaps and risk aversion, are slowing progress.

Bridging that gap means rethinking how the public sector approaches technology, from the way data is managed to how collaboration and innovation are encouraged across departments.

Legacy systems: the weight of the past

One of the most persistent obstacles to digital transformation in the public sector lies in legacy systems. In the UK, around 30% of central government IT systems are now classified as legacy.

In government, the impact of outdated systems goes far beyond minor technical inconvenience. When databases don’t connect, people end up re-entering the same information, teams build up manual workarounds, and citizens face clunky, inconsistent services.

True modernization starts with fixing the data foundations and building systems that are flexible enough to adapt as needs change. When information can move easily and securely between departments, public services can respond faster and make better informed decisions, while still protecting the privacy and trust that citizens deserve.

The human and organizational dilemma

But technology alone can’t bridge the gap. Much of the challenge lies in the way public institutions are structured and managed.

Departments often operate in isolation, tied to distinct budgets, objectives, and accountability frameworks. The result of this is that technology improvements made in one area may never reach another, even when they address similar problems.

Beyond rolling out new technology, delivering genuine end-to-end digital services in the public sector means tearing down the silos between operations, policy, and tech teams so that everyone is pulling in the same direction.

The government’s recent progress on a single digital identity system for citizens marks a welcome step towards that goal.

The initiative aims to replace dozens of disconnected sign-in processes with one trusted login across departments. It’s not a cure-all, but it shows what’s possible when different parts of government align behind a shared purpose and a user-first approach.

Real transformation also means shifting the mindset of the people within those organisational structures. Technology, citizen expectations, and policy priorities all evolve, and so must the services built on them.

That requires a culture of continuous innovation, where teams are empowered to experiment and adapt quickly when something isn’t working. The UK government’s success won’t necessarily depend on how quickly it digitizes, but on its ability to keep evolving - continuously listening to citizens and improving the services it provides.

AI as an enabler, not a shortcut

The exciting thing about AI is that it can help governments untangle long-standing problems, like connecting data locked in different systems, or automating routine work so teams can focus on people and strategy, or turning raw information into usable insight.

However, it’s vital to note that true transformation comes from using AI as a tool to enhance human decision-making, not replace it, and from embedding it within a culture that values experimentation, learning, and accountability.

Public attitudes underline why this approach matters. A tracker survey published by the UK’s Centre for Data Ethics and Innovation (CDEI) earlier this year shows awareness of AI is now near-universal: about 96% of people have heard of AI and around 71% say they could explain it at least in part.

Yet perceptions remain mixed, and concerns about security, surveillance, and accountability persist. While many expect AI to help in areas like healthcare and crime prevention, roughly four in 10 anticipate positive impacts, and around three in 10 expect negative ones. It’s clear the public is engaged, but still cautious.

Therefore, any government adoption agenda must earn trust, not assume it.

That’s why recent policy moves matter, not as proof the challenge is solved, but as signs of a system starting to mature. The UK’s AI Playbook, for instance, sets out 10 principles for the safe and responsible use of AI across government.

It’s an important step towards consistency, shifting departments away from isolated pilots and toward shared standards on transparency, human oversight, and ethical design.

But for these principles to mean something in practice, they’ll need to be applied beyond central government, across local authorities, agencies and delivery partners where the real complexity lies.

Meanwhile, the AI Opportunities Action Plan signals ambition at scale, mapping how AI could underpin future public services and infrastructure. It’s encouraging to see that agenda take shape, but policy alone won’t close the gap between vision and delivery.

That will depend on the same things that drive any successful transformation: clear leadership and collaboration, and an appetite for continuous improvement.

When done right, AI becomes an enabler of progress rather than a shortcut to it. It helps government teams adapt to change faster and deliver services that evolve with citizens’ needs. In other words, it’s about people and institutions using technology wisely, to build public confidence and lasting impact.

A pragmatic path forward

Closing the digital divide in the public sector will ultimately take more than investment. It needs sustained focus and a readiness to do things differently. The priorities are clear though. Government needs technology that cuts across boundaries and supports decisions grounded in real evidence.

It also needs the confidence to use new tools in ways that put people first. Progress, however, depends less on grand strategies and more on the everyday work of maintaining systems, supporting teams, and deciding what to improve next.

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