The United Kingdom is digitising public services at speed. In January 2025, the government introduced the AI Opportunities Action Plan for adopting AI to improve public services and economic growth. This agenda has evolved to focus on AI deployment at scale, rather than experimentation.
Change is most visible in spaces such as healthcare, transport, and digital governance: Across public healthcare systems in the UK, AI, machine learning, and real-time data capabilities are streamlining hospital administration, patient health record management, and even diagnostics. Replacing legacy systems with AI-powered digital infrastructure is lightening the administrative burden on healthcare practitioners, allowing them more time to focus on patient care. Public transit systems are using predictive, real-time capabilities to dynamically reroute congested networks and enable seamless multi-modal journeys, while infrastructure management companies are deploying predictive maintenance to keep bridges and railways in good repair. Even local councils are employing AI tools to automate a range of smart city planning tasks.
The difference is embedded AI
Digitisation is not new to UK public services, which have been modernising with the help of intelligent networks, connected devices, software platforms, etc. But now, they are accelerating transformation by increasingly embedding AI directly into their operations.
By leveraging AI and other technologies, every public service provider can streamline operations, improve citizen services, and deliver services at speed and scale. But success depends on how well they engineer their systems for embedding AI into citizen workflows.
As a first step, legacy assets must be modernised into cloud-native systems and AI-ready datasets. Instead of adopting standalone solutions, public service agencies should incorporate AI within operational workflows and end-to-end user journeys. But rampant digitisation also brings serious concerns around data security, governance, and model reliability. Hence, alongside embedding AI, digital public infrastructure must integrate Secure-by-Design (SbD) practices. AI, data governance, and resilient network architectures must be treated as foundational layers and systems engineered in compliance with national and global regulations.
Specifically, an autonomous yet secure infrastructure requires the following architectural components and governance mechanisms:
Embedded AI and agentic workflows: Public services should implement secure agentic AI solutions that act independently without compromising data privacy and sovereignty. AI-driven network intelligence helps identify threats as they emerge, route traffic intelligently, and ensure service quality.
Resilient network architecture/private 5G: Fragile public networks are vulnerable to security and operational risks. Private 5G networks provide ultra-low latency, higher bandwidth, and deterministic performance to support mission-critical, localised infrastructure services, while storing sensitive citizen data locally.
End-to-end data lifecycle governance: Public services deal with massive citizen data that they can protect by using Privacy-by-Design (PbD) frameworks – embedding cryptographic standards, zero-trust principles, and anonymisation protocols at the data ingestion layer – and by integrating policies with global security and accountability frameworks. Also, by using UK-based sovereign cloud platforms, public service departments can exercise full control over highly classified data while safely deploying AI and automation.
The most important thing is to implement AI responsibly. Public service departments cannot have their AI models functioning as black boxes; they need to build transparent, explainable, and auditable systems, especially in areas that directly impact citizen interest. Algorithms should be used to augment, rather than replace human decision-making. There needs to be human oversight and validation of critical automated decisions such as those related to taxation. In the interest of security and privacy, only essential information should be collected. Public services should embrace digital and intelligent technologies but always keep paramount the interests of the public they serve.
