Building AI Skills Across Government is no longer just about helping public sector teams understand new tools. As Professor Nisreen Ameen, explained in her session, it is about creating the confidence, capability and governance needed to use AI safely, effectively and inclusively across the workforce.
The session, delivered as part of the Government Technology and AI in the Public Sector Conference, is now available On Demand. It offers a timely look at what AI skills really mean in practice, why training often fails to keep pace with adoption, and how government can support more consistent workforce readiness.
Why AI Skills Matter Across the Public Sector
Nisreen’s presentation drew on collaborative work with Skills England, and Skills for AI: What works for AI upskilling in the UK exploring AI skills and workforce readiness across multiple sectors. While the research looked beyond government alone, its implications for public services are clear: AI is already embedded in everyday work, but many organisations are still relying on informal, inconsistent and fragmented training.
This creates a gap between access to AI tools and the ability to use them responsibly. Staff may already be using AI features built into common workplace platforms or experimenting with chatbots, but without structured guidance, organisations risk uneven capability, unclear accountability and missed opportunities for productivity and service improvement.
For public sector leaders, this is particularly important. Digital transformation depends not only on technology procurement, but on people having the skills, confidence and ethical awareness to apply tools in real-world roles.
Building AI Skills Across Government Requires Shared Language
One of the strongest themes from the session was the challenge of terminology. Nisreen highlighted that experts from industry, academia and policy often interpret “AI skills” differently. This lack of shared language can make it difficult for organisations to diagnose skills gaps, select training and understand what good practice looks like.
For government departments and public bodies, a clearer vocabulary around AI capability can help teams move beyond generic awareness sessions. Digital literacy should include technical understanding where relevant, but also responsible AI, ethics, compliance, inclusion, data awareness and the ability to collaborate across disciplines.
This connects closely with wider conversations about organisational readiness. For further insight into adapting to AI-driven change, Government Events has also explored building resilience in the age of AI, including lessons from industry experts.
Three Practical Tools for AI Workforce Readiness
A key part of the session focused on three tools developed through the research to help employers, including smaller organisations, plan their AI upskilling journey more effectively.
- The AI Skills Framework
The AI Skills Framework maps skills by job level across three domains: technical skills, responsible and ethical AI skills, and non-technical AI skills. It recognises that not every role needs advanced technical expertise, but every organisation needs a foundation of AI literacy.
For government, this approach is especially useful because AI capability must extend beyond specialist digital teams. Policy professionals, operational staff, managers, analysts and frontline workers may all need different levels of understanding depending on their responsibilities.
- The AI Skills Adoption Pathway
The adoption pathway outlines the stages organisations typically move through when adopting AI: awareness, exploration, assessment, experimentation, integration and scaling. This helps employers understand not only where they are now, but what they need to move forward safely and sustainably.
In public services, this staged approach can support more realistic planning. Rather than expecting teams to jump straight from curiosity to full implementation, leaders can build confidence gradually, align AI with strategy and ensure staff development keeps pace with deployment.
- The Employer AI Adoption Checklist
The checklist helps organisations assess their current position across areas such as strategic alignment, experimentation, skills, inclusion and responsible use. Professor Ameen emphasised that inclusivity should be designed into AI upskilling from the beginning, not added later.
This matters for government because digital transformation must work for diverse workforces and communities. If training is not accessible, practical and relevant, AI adoption may widen existing capability gaps rather than reduce them.
What Effective AI Training Looks Like
The second programme discussed in the session focused on a central question: what actually works when upskilling the UK workforce for AI?
The findings pointed to four features of effective training. It should be flexible and accessible, allowing staff to learn alongside day-to-day work. It should be practical and contextualised, focused on real tasks rather than abstract tool demonstrations. It should support recognition and progression, helping people understand how their skills develop over time. Finally, it should sit within a clear AI skills framework so employers know what good looks like.
This aligns with broader digital learning challenges across the public sector. Government Events has previously examined developing digital capacity for technology enhanced learning, highlighting the importance of embedding digital capability into learning design and organisational culture.
The PRIMES Framework: A Model for Sustainable Upskilling
Professor Ameen introduced the PRIMES framework as a foundation for effective AI training. In this model, training should be practical, reachable, integrated, modular, expandable and sustainable.
In simple terms, AI learning should not be a one-off course. It should be embedded into workflows, supported by leadership, reinforced through peer learning and connected to real use cases. It also needs to evolve as technologies, policies and organisational needs change.
The session made clear that governance and safe use must be built into training, but contextualised for different environments. What responsible AI means in health, local government, construction or social care will vary depending on the risks, data, users and decisions involved.
Lessons for Government Leaders and Policymakers
For employers and public sector leaders, the message is to move from informal experimentation to structured adoption. This means creating protected time for learning, setting clear rules for safe use and ensuring training is connected to real roles and responsibilities.
For training providers, the priority is flexible, modular and regularly updated provision. Training should be inclusive by design and relevant to sector needs, rather than generic or overly technical.
For policymakers, Professor Ameen highlighted the need for coordination, quality signals and clear progression routes. Frameworks, standards and employer needs must be aligned so that AI upskilling can scale across regions and sectors.
There is also a wider place-based dimension. Digital skills development can support stronger local economies and more resilient communities, linking to themes explored in Government Events’ article on coastal regeneration and recovery.
Conclusion: Turning AI Awareness into Public Sector Capability
Building Digital Literacy and Skills Across Government requires more than enthusiasm for new technology. It needs shared language, structured frameworks, practical training and a long-term commitment to responsible adoption.
Professor Nisreen Ameen’s session offers a clear message for public sector organisations: AI upskilling is not a single intervention, but an ongoing capability system. By embedding learning into everyday work, supporting inclusive access and linking skills to governance, government can build the confidence needed for safe, productive and people-centred AI use.
To explore the full discussion, watch the On Demand session from Technology and AI Innovation in the Public Sector 2026.