AI in local government contact centres isn’t replacing staff—it’s empowering them, says Afshin Attari, Senior Director of Public Sector at Exponential-e.

Within local government, the contact centre sits at a pivotal crossroads. For many residents, it's still the first, and sometimes only, point of contact with local services, yet the scale and complexity of what these teams are asked to handle daily would be staggering in any commercial context.

Where else might a single agent field enquiries ranging from waste collection and council tax to adult social care and business rates, sometimes all within the same hour? A frontline agent could be hit with over 90 different types of queries, each one potentially requiring contextual understanding, fast access to accurate data, and a calm, empathetic approach.

The challenge, then, is not simply volume. It's about delivering timely, effective responses across a dizzying range of services, at a time when both human resources and financial headroom are diminishing. Add to that the growing vulnerability of citizens seeking support, and the emerging complexity of local government reorganisation, and it becomes clear that the traditional contact centre model is no longer sustainable on its own.

AI as an enabler, not a replacement

In a Local Government Association report, released earlier this year, which surveyed a third of UK councils,95% claimed that they were using or exploring AI.

This is where AI can add real value to councils within the contact centre; not as a replacement for human agents, but as a critical enabler of their success.

There is, understandably, some trepidation throughout the public sector when it comes to AI adoption. Concerns around hallucinations, data integrity, or AI ‘replacing’ human jobs are valid. But these fears risk obscuring the real opportunity: using AI to surface the right data, at the right time, in the right format, so that the human on the end of the line can focus on what they do best.

AI in local government usually centres around speculative use cases or generalised chatbot deployments, but we're talking about deeply embedded tools that analyse live conversations across channels, recognise intent, and aggregate relevant case histories, verification details and contextual documentation, sometimes even before the agent answers the call. When deployed responsibly, AI doesn't guess. It informs.

The result? First-contact resolution rates improve, hold times drop, staff are less overwhelmed, and citizens get answers instead of further referrals.

Meeting citizens where they are

Modern contact centres must be multichannel by default to avoid digital exclusion. Phone calls remain vital to service an entire community made up of different demographics, particularly for complex or sensitive issues, but residents increasingly expect service availability across email, webchat, SMS, and social platforms as well.

This shift isn’t just generational - it’s circumstantial. Vulnerable users may find it easier to chat than call and others may seek assistance outside of core hours via email or other 24/7 channels.

Effectively manually monitoring all of these different platforms is near impossible, but crucially, AI enables consistency across these channels. If a resident sends an email at 9pm and calls the next morning, the agent should already have that context at their fingertips. It's only through integrated, AI-enhanced platforms that such seamless continuity becomes possible.

Real-time analytics

Historically, local authorities have had to manage service quality reactively, spotting issues only after complaints or performance metrics were reviewed days or weeks later.

AI offers an entirely new model. With the right tools in place - data on wait times, call transfers, resolution rates, and citizen satisfaction can be accessed and acted upon in real time.

Dashboards that refresh every few seconds allow supervisors to intervene before small issues become systemic problems. They also enable progressive improvements in other areas such as refining call flows, updating knowledge bases, and reallocating staff dynamically based on demand.

In a sector where public trust and service equity are paramount, this level of insight is invaluable.

Measuring AI readiness

Of course, technology is only one part of the puzzle. For AI to deliver on its promise, local government organisations must first get their data house in order.

This means consolidating disparate systems, enforcing rigorous governance policies, and ensuring data is clean, secure, and accessible. But it also requires a cultural shift. One that embraces experimentation, feedback loops, and a more agile, outcome-led approach to service delivery.

Many councils are already on this journey, often as part of broader cloud transformation initiatives. The contact centre, with its rich stream of citizen interaction data, is arguably the most strategic starting point for AI implementation.

Liberating, not replacing, the human touch

Ultimately, the success of AI in local government contact centres won’t be measured by how many queries it can automate, but by how effectively it empowers staff to deliver better outcomes for citizens.

By handling the heavy lifting, AI frees agents to focus on empathy and problem-solving. And in services like adult social care or housing support, those human qualities are irreplaceable.

As local government continues to evolve through structural reorganisations, increasing devolution, and shifting citizen expectations, contact centres must not be left behind. They must evolve into intelligent, responsive, citizen-first service hubs where technology supports, rather than replaces, the human connection.

The AI-powered contact centre is not a distant ambition. It is here. And for local government, it might just be the most transformative step they can take in delivering an improved, fairer, and more efficient public services to its constituents.

To find out more about how local authorities are deploying AI, check out: 10 Ways Councils Are Using AI to Transform Public Services