People and learning for AI at work

Start with what people need to accomplish in their work. Choose specific tasks, the skills they require and how you will check that the new practice helps.

What to learn

• Working with AI: foundations — capabilities, limitations and checking results.
• AI literacy — understanding tools, context and risks.
• Giving AI a clear task — context, inputs, expected results and verification.
• Comparing AI tools — choose for the task and data.

How to prepare learning

Record target tasks, current experience and permitted tools. Prepare examples people can safely use. At the end, ask participants to complete a task independently and explain how they checked the result.

• Training plans and records — preparation, delivery and evidence of measures taken.
• Courses and their purpose — programme choices and what certification means.

How to put learning into practice

Follow training with time to practise, support when people get stuck and a review. Involve someone who coordinates the work and the people who decide on tools and process changes. Agree responsibilities inside the organisation.

• Planning AI adoption — purpose, people, processes and technology.
• Questions and concerns about change — communication and participation.
• Coordinating AI use — mandate, collaboration and responsibility.
• Measuring benefits — baseline, cost, quality and actual use.

Training and practical workshops can be adapted to your team. The relevant course page explains each programme’s terms.