AI in the Public Sector: Transforming Government and Healthcare

AI is viewed primarily as a productivity tool within public sector, but there’s a growing interest in how it can become transformational for local government and healthcare. AI has the ability to improve citizen outcomes and efficiency, but progress with implementing the technology depends on people, governance, and trust.

Our Public Sector 2.0 roundtable roadshow brought together leaders from local government and healthcare in London and Manchester to discuss how to build the right foundations for AI adoption. Leaders explored how opportunities with data, AI, cyber and quantum can drive business transformation in public sector organisations. The discussions revealed a shared determination to modernise operations, but also a recognition of the significant challenges that must be addressed first.

Across every conversation, a key theme stood out: AI success depends as much on people and governance as on technology.

Public sector organisations are eager to harness AI, from the NHS using diagnostics tools to councils exploring automation. But trust, data quality, and security remain the biggest barriers to adoption.

Attendees highlighted that progress often stalls because:

• Governance frameworks are still evolving, leaving uncertainty about accountability and ownership.
• Data quality and fragmentation limit how confidently AI can be deployed.
• Skills gaps and trust issues slow down adoption, as teams question AI’s impact on roles and responsibilities.
• Siloed initiatives lead to duplication of effort and missed opportunities for collaboration.
• Teams are too busy fighting fires to invest in long-term change or AI implementation.

Despite these challenges, there was strong optimism across both groups. Leaders agreed that by starting small, demonstrating measurable value, and embedding security and governance into everyday operations, organisations can build both confidence and momentum.

AI offers the potential to significantly improve accessibility and outcomes across public services.

In healthcare, AI-driven discharge management can help predict patient discharges, reduce bed occupancy, and coordinate social care packages more effectively, improving outcomes for patients and easing pressure on staff.

In local government, a key use case highlighted at both events FOI automation, automating the process of receiving, analysing and responding to Freedom of Information requests. This type of agent would enable faster, more consistent and compliant handling, improving citizen experience and freeing staff to focus on complex or sensitive requests.

Across public sector, predictive workforce planning using AI to forecast staffing needs, could be beneficial. This would ensure resources are available where and when they’re most needed.

AI can strengthen decision making by creating smarter, data-informed governance across the public sector.

One area of focus was the potential to standardise information governance (IG) across organisations, ensuring consistency, compliance, and easier data sharing.

Other opportunities include:

• Automating risk management to identify and respond to emerging issues faster.
• Using AI tools to analyse financial and operational data for greater efficiency.
• Reducing duplication in bureaucratic processes through intelligent automation.

By integrating AI into governance processes, councils and NHS organisations can build more transparent, efficient, and citizen-focused services.

Innovation in AI must be balanced with strong ethical and governance practices. As one London participant put it, “If you wouldn’t put it in an FOI, don’t give it to AI.”

Participants at the Manchester event, felt that the speed of innovation outpaces organisational and national governance, hindering confidence in AI implementation. Security should be an enabler for innovation, not a blocker.

Key priorities include:

• Implementing clear data governance frameworks.
• Embedding cyber security at the architecture stage, not added in later.
• Standardising access control and data-sharing agreements.
• Promoting staff awareness and confidence through training and transparency.

By embedding security and data governance teams within operational environments, organisations can empower innovation safely. This approach not only reduces risk but also encourages a culture of responsible experimentation.

Looking ahead, the message from is clear: AI is here and the public sector must safely embrace it, or they will be left behind. As one participant from Manchester put it “AI is not coming for your job, someone who know how to use AI will.”.

To succeed, organisations should start with targeted use cases that deliver visible benefits, laying the groundwork for broader adoption. With the new National AI Policy, collaboration between central and local government will be key to ensuring consistency, governance and avoiding a fragmented approach.

By sharing successes, frameworks, and lessons learned, the public sector can accelerate AI adoption, moving from isolated pilots to scalable, sustainable transformation.

So, what’s next?

Celerity and IBM Client Engineering are here to help organisations identify practical use cases, develop governance frameworks, and demonstrate measurable outcomes from AI.

Want to discuss the possibility of AI in your organisation? Book a meeting with one of our experts.