Agentic AI technology can transform complex processes and help the civil service deliver a higher quality human service to citizens. At Capita we’re testing use cases to lead the way forward.
I joined Capita in December 2024, and in a short space of time I’ve learned a great deal about the needs and expectations of public service delivery. In March 2025 we conducted a survey about AI agents with over 2,000 UK citizens: 52% said they have heard of AI agents and know at least a little about it, and 28% think AI agents will make services quicker or save time.
A quick history of AI
What we call AI today began as process automation in the 1950s. Predictive forecasts became possible in the 1980s based on huge amounts of historical data. In 2022, OpenAI’s ChatGPT demonstrated that it could generate human-like text and respond to everyday language. AI-powered tools like GitHub Copilot have transformed coding by turning natural language prompts into code. And AI chatbots are now widely used in customer service, providing instant, conversational responses to queries, reducing wait times, and improving user experience.
Introducing agentic AI
But one of the most interesting new developments is ‘agentic AI’ which is goal-orientated, can analyse situations, make decisions, and act independently to achieve a defined objective. By taking over repetitive, time-consuming tasks, agentic AI allows government employees to focus on human-centred work. The opportunity lies in having agents assist the values driven, service-oriented human who today delivers the end service to citizens. Most citizen-oriented tasks require a great deal of manual processes that today slow down the end delivery. By ameliorating these tasks, agents can help deliver faster, more accurate service by the human. These human agents have oversight and control of agentic AI and can task it with specific responsibilities, which it will do without needing more prompts.
Here are a few examples of how agentic AI can revolutionize the civil service:
- AI-Enabled Assessments: AI can assist in evaluating applications and documents, ensuring they meet policy requirements and flagging potential fraud attempts. This enhances the accuracy and efficiency of the assessment process.
- Citizen-Centered Services: Agentic AI can provide real-time support through chatbot interfaces, helping citizens understand service eligibility, complete applications for grants or benefits, and comply with obligations like council tax.
- Speed to Serve: AI agents can process application checks, flag issues for assessors, and handle first-line support for citizen enquiries, significantly reducing response times and improving service delivery.
- Outcomes-Based Approach: AI can summarize complex cases, such as benefits claims involving long personal or medical histories, to support human assessors in making informed decisions.
- Efficiency and Value for Money: AI can automate back-office workflows, manage application or personal detail changes, and support auditors in reviewing assessment performance and service quality, leading to cost savings and improved efficiency.
An AI-enhanced future
It is likely that in the next few years, civil servants will be managing AI agents as part of their teams. These AI agents will perform highly specific tasks, and employees will be able to refine and perfect their performance based on analytics and feedback from civil servants and citizens.
To start the agentic AI journey, there are many opportunities for automating processes that the civil service can start exploring and testing now, in partnership with an expert in complex, human-centric process management like Capita.
Our ambition is to be the UK’s go-to partner for executing complex process improvement with the right implementation of AI at the right time. So, to practice what we preach, we’re starting with our own processes. We’ve recently launched the AI Catalyst Lab, focused on identifying, testing and scaling AI solutions that drive measurable business outcomes.
For example, the Lab has recently launched a high-volume recruitment accelerator to enable candidates to find jobs that fit their needs, assess thousands of CVs in seconds, and narrow the candidate pool for a potential match.
The Lab’s initiatives are projected to enhance decision-making, reduce operational costs and improve overall service quality within Capita. At the same time, the AI Catalyst Lab will support our clients in adopting AI technologies, driving productivity gains and enabling them to stay competitive.
What opportunities do you want to explore?
In just the first month, the AI Catalyst Lab identified a pipeline of over 150 AI use cases, from learning and workforce development, contact centre transformation to fraud detection, collections and debt recovery.
But we want to listen to our customers and understand their requirements today and looking to the future. We are laser focused on helping our customers amplify the impact of human-centric processes with AI technology – in other words, supporting people to deliver better services to citizens.
So, we want to hear from you: what are the processes you manage that could be more efficient or effective? Where are your citizens experiencing pain points? What is costing more time and money than it should? What would make your job easier?
By starting with questions like these, we can help make agentic AI a powerful and positive tool for civil servants and citizens alike.
Got any questions or ideas? Reach out to us at bettergovernment@capita.com We’d love to hear from you!

Sameer Vuyyuru
Chief AI and Product Officer
Sameer is responsible for overseeing and accelerating Capita’s AI, product and solution strategy and leveraging our hyperscaler relationships. Delivering scalable, repeatable AI solutions underpins Capita’s strategy to deliver better client outcomes. Sameer brings over 25 years’ experience in the global technology sector including, most recently, his role at Amazon Web Services (AWS) as Director, Global Solutions and Partnerships, Telco and Edge Strategy, as well as senior roles with Comtech, Semtech, Intersil and Texas Instruments.