Workforce Training

AI literacy is a baseline for your entire workforce. People across operations, finance, sales, HR and other functions need to understand what AI can help with, where it can fail and what remains their responsibility. No engineering background is required.

Start with a real task. What problem are you trying to solve? What information does AI need? What information should you withhold? How will you check the result before someone relies on it? These questions give people a practical basis for using AI in their own work.

Choose the right starting point

The AI Literacy Workshop is a focused introduction to how AI works, prompting and context, and the judgement needed to use its output.

AI Literacy & Foundations develops that grounding further through practical work with organisational context and role-specific AI use. Follow the course links below for each curriculum. Both serve the wider workforce.

If you are arranging training across the organisation, start with the roles involved and the work they need to do. Choose leadership alignment when leaders need to agree purpose, information boundaries and responsibility. If you already have a specific problem to investigate, you can go directly to AI Opportunity Discovery. Training is not a prerequisite for that conversation.

If Article 4 brought you here

As checked on 14 September 2026, Article 4 requires providers and deployers within scope to take measures supporting AI literacy development, taking account of people’s experience and the context of use. It does not require a guaranteed literacy level for each individual. See the current EU legislation.

Training can contribute to those measures. A certificate alone does not establish that an organisation has met its obligations. Your legal or compliance lead should assess scope and the evidence your organisation needs.

What people take into their work

A shared language for discussing AI, practice giving it useful context, and a habit of checking output before acting on it. Build on that baseline with guidance for the systems, information and decisions each role handles.

Put the learning to work

In AI Literacy & Foundations, participants practise prompting, describe their role in a context block and receive a prompt for a personal AI assistant. That exercise provides a starting point for using role context; it does not establish that an assistant is ready for operational use. Applying it to an organisational workflow also requires an owner, agreed information boundaries and checks before anyone relies on the result.

Choose one task and define what acceptable work looks like. Use information you are permitted to share, check the output against its sources and follow what happens after it leaves the person who created it. Include the time spent reviewing and correcting it when deciding whether the change helped.

Assign someone to keep the supporting information current, review failures and decide when use should stop. Written instructions communicate expectations; access restrictions and checks must support them. An assistant that helps you prepare work and an agent authorised to act on a system need different controls. Engineering support is available when permissions, integration or recovery need technical work.

If AI work is already creating rework, or its use is unclear, start with the problem you can see. You do not need a measurement system in place before asking for help.