AI in Government: From Ambition to Execution
AI and automation are no longer distant goals. They're practical levers to deliver faster, fairer, more efficient public services-right now.
With £3.25 billion committed in the 2025 spring statement and a clear AI Playbook to guide adoption, the intent is there. Yet only 26% of departments have integrated AI across their organisation. Legacy systems, siloed data, and fragmented procurement are still slowing progress.
The next phase is about execution: connecting systems, equipping people, and scaling what works-safely.
Why execution is stuck
- Data is trapped in departmental silos, blocked by organisational, technical, and governance boundaries.
- Procurement is still geared to big, rigid contracts and external consultants-slowing delivery and removing know-how from teams.
- Digital spend keeps rising (over £14 billion per year), but outcomes lag. Despite more than £26 billion in annual digital and data spending, a quarter of services are outdated and nearly half aren't digitised.
Break silos with interoperable infrastructure
Most departments are sitting on valuable data. The issue isn't volume-it's movement. Too often, incompatible platforms and outdated processes block secure, efficient data flow.
The fix is an interoperable foundation: common data standards, APIs, and trusted exchange protocols. AI should share answers-not raw, sensitive data-within strict, auditable boundaries.
Agentic AI can put this into practice by finding the right information across systems, taking routine actions, and advancing processes end-to-end. Do this well and you'll reduce duplicate requests, speed up delivery, and free staff for higher-value work. Smarter use of linked data could lift public sector efficiency by up to 20%.
- Adopt shared data models and API-first design for new and upgraded systems.
- Introduce secure data exchange patterns (query/response over copy-and-store).
- Set auditable guardrails for AI actions, approvals, and escalation.
Equip civil servants for the digital era
Technology won't deliver outcomes without people who can use it with confidence. Many teams lack the tools, training, and AI literacy to implement at pace.
Keep a strong human-in-the-loop model for trust, security, and quality-especially in high-stakes services. Shift away from rigid procurement that locks knowledge outside departments.
In a trial with 20,000 civil servants, AI tools for routine tasks saved roughly two working weeks per person per year. That time goes back into service quality, casework, and policy delivery.
- Stand up short, practical AI fluency programs for leaders, delivery teams, and operations.
- Provide accessible tools (no-code/low-code, secure AI assistants) and clear usage policies.
- Rework procurement to build internal capability, reduce dependency on external consultants, and retain institutional knowledge.
If your team needs a fast on-ramp to AI literacy, explore role-based training options here: Complete AI Training - Courses by Job.
Scale reusable AI assets
Too many departments rebuild what already exists. The result: duplicated effort, rising costs, and slower delivery. NHS England once ran around 50 different CRM platforms before restructuring-this pattern repeats elsewhere.
Shift to reuse. Build a central repository of proven AI components: models, prompts, workflows, connectors, and APIs. Pair it with procurement rules that prioritise reuse, modularity, and interoperability.
- Publish reusable components with clear documentation, security profiles, and performance metrics.
- Standardise interfaces so components plug into existing systems with minimal custom work.
- Use purchasing power to favour products and vendors that support open standards and composable architectures.
A practical 90-day plan
- Weeks 1-3: Pick three high-volume, rules-based processes. Map the data flows and pain points. Define guardrails for AI use.
- Weeks 4-6: Stand up a secure sandbox. Pilot agentic AI for document handling, triage, and case updates. Keep humans in the loop.
- Weeks 7-9: Introduce shared APIs for key data sources. Replace copy-and-store with query-and-answer patterns.
- Weeks 10-12: Package what works into reusable assets (workflows, prompts, connectors). Publish internally with documentation, KPIs, and a maintenance owner.
- Measures of success: 20-30% faster cycle times on pilot processes, fewer duplicate data requests, reduced rework, and staff time saved.
Deliver on AI ambition
The UK has set bold goals for AI in public services. Turning that into impact depends on execution: modern infrastructure, skilled people, and reuse at scale.
Do the simple things well. Connect systems. Keep people in control. Build once, use many times. If departments align intent with consistent action, AI won't just make services more efficient-it will help create a public service ready for what's next.
Your membership also unlocks:
