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Technology Assessed, People Equipped: Building AI Capability Across 50,000+ Civil Servants

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Technology Assessed, People Equipped: Building AI Capability Across 50,000+ Civil Servants
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Overview 

Over 50,000 civil servants shared one ambition: to become an AI-enabled workforce where every member of staff could use AI to improve productivity and drive innovation. To realise that ambition, the Department first needed to understand the current levels of AI competence, confidence, and sentiment across the workforce, in order to define a clear strategic roadmap for AI skills development and responsible adoption. To realise that ambition, the department first needed to understand workforce AI readiness across all functions and grades — establishing where people were starting from before defining where they needed to go.

North Highland combined strategic workforce planning and AI capability development expertise to segment the ~50,000‑strong workforce, establish a robust baseline of AI capability, and design targeted AI learning pathways and change interventions. Together, these learning and change interventions defined the requirements for building sustainable AI capability and enabling consistent, responsible adoption across the Department.

At a Glance

50,000 Civil servants with access to structured, persona-specific AI learning pathways
10,500+ Survey respondents providing the evidence base for the capability assessment
6 Persona-specific learning pathways built, tested and integrated with existing digital infrastructure
45 Learnings per pathway, representing 8hrs of curated learning for all staff

The Situation

The Department had set itself a set of ambitious goals. Its 2030 Digital Strategy committed to transforming its digital services using AI and increased automation, signalling AI as a core enabler of future service delivery rather than an emerging or experimental capability.

However, AI workforce development was constrained by two systemic issues: an overreliance on a onesizefitsall AI capability model that failed to reflect diverse operational, functional, and strategic use cases, and the absence of a centrally defined AI people and capability strategy. As a result, the AI training provision was fragmented and poorly targeted, leading to inconsistent engagement with AI and significant variation in AI skills, capability, sentiment and adoption across its workforce.

What the department required was a structured AI learning needs analysis: a rigorous, data-led process to baseline current capability, identify gaps, and design targeted learning that would translate into lasting behaviour change.

The true value of AI is realised not by technology alone, but by the skills, behaviours, and change required to embed it into everyday work.

The Department needed a partner who could quickly baseline current AI skills and sentiment, and design a persona-based AI learning framework, enabled by targeted change interventions and underpinned by proportionate, sustainable governance.

Our Approach

North Highland structured the project across two phases: "Analyse and Plan," where we assessed existing AI competency, sentiment and priority use cases across the organisation. Next was "Develop, Test and Learn," where we designed and validated tailored AI skills frameworks and learning pathways aligned to the diverse operational, functional and strategic needs of the workforce. The capability assessment prepared the ground, the learning design enabled the skills to take root.

What made it work was the integration of technology and talent at every stage. We used digital survey tools to capture workforce insights at scale, and advanced analytics transformed responses into robust, actionable insights directly informing AI skills design and learning pathway development. Expert learning design and people-centred change management then converted insight into six distinct learning pathways that would resonate with real roles and lived experiences. Neither dimension alone would have delivered a learning programme that was both evidence-led and genuinely relevant to staff.

Capability Baselining at Scale

Generating insights from 10,500+ survey responses across the organisation enabled us to establish a clear, evidence-based picture of current AI competency, confidence and readiness for change. This was not a top-down view: it reflected the real experience of staff across every function and grade, giving a statistically grounded baseline for the first time.

Persona-Based Learning and Change Design

We developed and validated six bespoke workforce personas. Each persona captured the defining characteristics of a defined group of the workforce, documenting their goals and motivations, pain points and challenges, relationship with technology, and learning preferences. These personas became the foundation for designing tailored, personaspecific learning pathways and change interventions, ensuring capability development was grounded in real role contexts and user needs. This was expert design work, not template delivery: every pathway reflected the starting point, behaviours and expectations of the people using it, from frontline officers to strategic leaders.

Each learning pathway was supported by tailored learning interventions, curated to meet the specific needs of each persona group, moving beyond generic content to ensure every learning journey reflected the starting point, priorities, and working patterns of the people following it.

AI Skills Framework: Technology Grounded in Behaviour

North Highland built an AI skills framework specific to the Department and its key workforce personas: proficiency levels, key behaviours, skills and competencies, grounded in discovery findings rather than generic best practice. The framework gave the organisation a shared technical and behavioural language for AI capability, built on the understanding that AI adoption demands both technical proficiency and cultural readiness in equal measure.

Built on survey findings, departmental goals, and sector best practice, the framework set out a clear skills pathway from Unaware through to Expert, giving every role a defined route for developing AI capability in the context of their day-to-day work.

Crucially, the framework went beyond skills and proficiency levels. In a government context, responsible AI adoption requires more than capability building. The skills framework explicitly addressed safe and secure AI use, equipping staff to identify risks, apply appropriate governance, and adopt AI in ways that protect data and uphold departmental security standards.

Sustainable Learning Architecture

North Highland curated existing learning content into six bespoke learning pathways and integrated these within the Department’s digital skills academy, enabling staff to access AI learning through a familiar platform and accelerate uptake. Builtin metrics were designed to measure engagement and effectiveness, capturing participation, progression, and outcomes, while automatically updating individual learning records to support ongoing insights into workforce skills. A robust but proportionate governance model was developed to ensure the pathways remained current and clarified roles and responsibilities as the learning pathways transitioned into BAU.

Value Delivered 

The programme delivered results at three levels: a robust evidence base the Department had never held before, a scalable infrastructure for AI learning, and the cultural foundations needed to make it stick.

Evidence

For the first time, the Department had a statistically grounded, comprehensive picture of AI competency, sentiment and workforce readiness. The findings were telling: AI literacy scored 2.5/5 on a Likert scale, sitting between Aware and Working level, and relevance to role emerged as the lowest scored dimension for learning opportunities. These were not comfortable numbers, but they were exactly the honest baseline needed to design learning that would make a real difference.

Infrastructure

Six persona-specific learning pathways were built and made available to over 50,000 civil servants, each supported by 45 tailored learning resources and 8 hours of structured learning. All six pathways were integrated with the Department's existing digital upskilling platform, ensuring staff could access AI learning through a familiar environment and removing barriers to uptake from the outset.

Culture

The programme was designed from the outset to address more than knowledge gaps. Change materials built to foster trust, establish psychological safety and secure leadership sponsorship ensured AI learning was embedded as a sustained priority, not a one-off initiative.

The Department now holds what it lacked at the start: a technology-grounded evidence base, a people-centred skills framework, and six tailored learning pathways designed to move every member of staff from unaware to confident. That is what becomes possible when technology assessment and talent development are treated as one investment, not two.

“We brought North Highland in to assess AI skills and sentiment across our ~50,000-person workforce and to develop a skills framework to build AI literacy and confidence. Their work provided a clear baseline and set of learning pathways and change materials tailored to the diverse needs of our workforce, giving us a groundwork to accelerate the development of an AI-enabled workforce.”
Senior UK Government Leader

Frequently Asked Questions

What is an AI Learning Needs Analysis? An AI Learning Needs Analysis (AI LNA) is a structured assessment that maps the current AI capability, confidence and readiness of a workforce using survey technology and capability frameworks. It identifies gaps between where people are today and where they need to be, then uses those findings to design targeted learning pathways. Rather than deploying generic training, an AI LNA ensures that upskilling is grounded in real data, designed for specific roles, and built to translate into behaviour change rather than just content consumption.
How do you assess AI capability across a large workforce? At scale, the most effective approach combines survey technology for breadth with people-centred design for relevance. Surveys establish a quantified baseline across the whole workforce. Persona development then ensures the findings translate into learning experiences that are relevant to each role, working pattern and starting point. Technology captures the evidence; learning design turns it into something people will actually use. Each is necessary; neither works without the other. 
What is a persona-based approach to AI upskilling? A persona-based approach groups employees into profiles based on how they work, what they need from AI, and what their current capability looks like. Instead of a single training programme applied across the whole organisation, each persona receives a pathway designed around their specific role and starting point. For a workforce as diverse as a major government department, this is what makes the difference between training that is completed and training that changes how people work.
How long does an AI capability programme for a large organisation take? For large organisations with diverse workforces, a phased approach typically works best: an initial analyse-and-plan phase to establish the baseline and define learning requirements, followed by a develop-and-test phase to build, validate and deploy pathways. The duration depends on the scale of the workforce and the complexity of the role landscape. For a 50,000-person workforce, programmes of this kind typically run between four and six months, depending on workforce scale and complexity.

Ready to build AI capability across your workforce? Get in touch.

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