- Employees do not need to code; they need to give clear instructions and check results.
- Train with real tasks from each department, not generic demonstrations.
- Pair training with clear rules on which tools and data are allowed.
As AI tools spread through every department, the gap between staff who use them well and staff who do not is becoming a productivity gap. The good news: the core skills can be taught in weeks.
Five practical skills
- Writing clear requests: stating the task, the context, the format and the audience.
- Providing source material: attaching the policy, template or previous example rather than hoping the AI knows.
- Checking outputs: verifying facts, numbers and names before anything is sent or filed.
- Breaking work into steps: using AI for drafting, summarising or checking, while keeping judgement with people.
- Handling data safely: knowing what information must never be pasted into which tool.
How to build them
Run short sessions by department using real tasks: finance staff summarise a contract or reconcile a statement; sales staff draft follow-up emails from meeting notes; HR staff prepare interview guides. Follow up with a shared library of good prompts and examples.
Appoint an "AI champion" in each team, someone who is enthusiastic and respected, to help colleagues and collect ideas for automation.
Rules first
Training without guidance on approved tools and data creates risk. Publish a simple internal AI policy covering which tools are allowed, what data may be entered, and how outputs must be reviewed. In Hong Kong, the Privacy Commissioner's guidance on employees' use of generative AI is a useful starting point; see our summary.
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