Annex B: Use cases: How organisations can use the AI Skills Framework
Published 29 October 2025
Applies to England
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The following examples illustrate how individuals or organisations might use the framework itself, not just apply AI skills, but actively draw on the framework to plan, assess, or support workforce development and responsible AI use.
An SME owner planning AI adoption
A small and medium sized (SME) owner running a small health and wellbeing clinic is assessing how AI could support daily operations, exploring automation tools like AI-based appointment booking systems, automated transcription tools for client notes, and simple dashboards created through low-code platforms. They use the framework to map their team’s roles to entry- and mid-level AI skills to clarify roles and identify what foundational training is needed. For example, identifying who will be writing prompts for AI tools (technical), identifying bias in AI outputs (responsible), and applying new AI tools to support daily tasks (non-technical).
The framework helps them to:
- prioritise simple, cost-effective tools they have the skills to use for immediate effect
- identify where there are skills gaps for individuals and teams as they take on new AI related roles
- put in place appropriate training, including informal peer learning
- recognise when external expertise is needed
- embed responsible AI principles early as the business scales up
Construction firm integrating AI into site operations
A regional construction firm is exploring the use of AI tools to improve safety monitoring and project scheduling. The operations manager uses the framework to assess and improve AI readiness across different job levels:
- site supervisors are mapped to entry or mid-level skills using embedded AI in safety checklists and recognising biased or unreliable outputs
- back-office staff are supported to apply low-code AI tools for reporting and materials tracking
- senior managers use the framework to guide investment decisions in AI skills training and oversee responsible deployment
The firm is trialling tools such as AI-enabled video analytics for on-site hazard detection and predictive maintenance systems that use sensor data to anticipate equipment faults. These applications involve a mix of AI skills aligned to the AI skills framework.
Entry-level staff:
- technical: operate embedded AI features
- responsible: assess accuracy and appropriateness of AI for tasks
- non-technical: apply new AI tools to support daily tasks
Mid-level staff:
- technical: use low-code AI platforms for automation; create basic dashboards or scheduling tools using AI features
- responsible: assess AI outputs and apply professional judgement
- non-technical: use AI insights to improve service provision or decision-making
Managers:
- technical: manage AI integration into core service provision processes
- responsible: guide ethical use of AI systems using policies and standards
- non-technical: use AI tools aligned with team or service objectives
The framework helps the firm ensure that:
- AI use enhances rather than disrupts workflows
- ethical, health and safety, and data protection concerns are addressed
- upskilling plans are realistic and role-specific across both site and office functions
Use-Case Personas
The following are illustrative examples of how individuals at different job levels might apply the AI Skills Framework in their day-to-day work. These personas are not exhaustive but are designed to show how the framework can guide practical upskilling across a range of contexts.
Entry-Level persona – Jake, Customer Support Officer at a local council
Scenario:
Jake responds to service requests and emails from residents. He starts using an AI tool to help summarise long communications and draft follow-up emails.
Within the AI skills framework, Jake identifies he requires the following skills:
- write prompts for AI tools to summarise messages and draft replies (Technical)
- assess accuracy and appropriateness of AI-generated responses (Responsible)
- use basic AI tools to complete routine tasks (Non-Technical)
Mid-Level persona – Claire, Training Designer in a healthcare trust
Scenario:
Claire supports clinical teams in designing training modules for new digital health tools. She is piloting a tool that generates role-specific learning content, quizzes, and case simulations.
Within the AI skills framework, Claire identifies she requires the following skills:
- use AI tools in lesson development workflows (Technical)
- evaluate AI-generated learning content for relevance and accuracy (Responsible)
- apply the new AI tool and guide peer learning (Non-Technical)
Managerial Level persona – Thomas, Head of Digital Strategy at a retail bank
Scenario:
Thomas leads a team integrating AI into fraud detection and compliance monitoring. He ensures adoption meets ethical, regulatory and strategic requirements.
Within the AI skills framework, Thomas identifies he requires the following skills:
- manage AI integration into core service provision processes (Technical)
- manage GDPR and data ethics compliance in AI-supported processes (Responsible)
- plan AI strategy and responsible use guidance across departments (Non-Technical)