What AI training do leaders need?

Enough hands-on use to be credible

Leaders do not need to be expert users of every tool. They do need to have used AI on real work, enough to understand what it does well, where it fails and how long a useful result actually takes. Without that, decisions about investment, risk and expectations rest on supplier demos and second-hand opinion.

• Use it on your own tasks: Outline a board paper, summarise a long contract or prepare questions for a supplier meeting using an approved tool, then check the result critically.

• Sit with a team for an hour: Watch how someone in finance or operations uses AI day to day, including the workarounds and frustrations.

• Try the failure cases: Ask the tool something you already know the answer to, and see how confidently it can get it wrong.

What leaders need beyond the tools

Setting direction

Leaders decide which problems AI should help with and which it should not touch. That means linking AI use to business priorities, such as faster turnaround on client deliverables or less time on internal reporting, rather than adopting tools because competitors have. If you are still deciding where to begin, see where to start with AI.

Judging risk

Leaders carry accountability for how AI is used. They need enough understanding to weigh data protection, client confidentiality, accuracy and reputational risk, and to know when to bring in specialist help. Where legal or regulatory duties apply, take advice on your own situation.

Questioning suppliers

Many AI decisions arrive through software vendors. Leaders should be comfortable asking direct questions.

• Data use: Where does your data go, is it used to train models, and who can access it?

• Evidence: Can the supplier show results from organisations of a similar size and sector, and can you speak to them?

• Exit: What happens to your data and workflows if you stop using the product?

• Accuracy: How does the supplier test outputs, and what happens when the tool gets something wrong?

Modelling sensible use

Staff watch what leaders do more closely than what they say. A director who openly uses AI to prepare, and mentions where they checked or rejected its output, shows the team that careful use is expected. A director who only mentions AI in strategy presentations sends a different message.

The cost of delegating it entirely

Handing AI wholesale to IT or a keen manager is tempting for a busy leadership team. The signal it sends is that AI does not merit senior attention. Staff notice, and cautious colleagues become more wary when leaders appear uninvolved. Engaging those concerns directly is covered in how to get sceptical staff on board with AI.

Delegating delivery is fine. Delegating understanding and accountability is not.

Shaping leadership training

Effective leadership training is usually short, hands-on and built around the decisions the team actually faces. A session that works through a real supplier proposal or a live risk question does more than a general overview of what AI can do. Leaders also benefit from training together, so they reach a shared view on priorities and risk appetite rather than forming separate opinions in isolation.