AI governance training

A useful session follows a proposed AI use from request to review. Participants identify the intended user, affected people, information involved and consequences of a misleading output. A document summariser and an automated customer decision require different discussions; a single generic checklist can conceal that difference.

Build a simple use-case record with an owner, purpose, limits and review date. Connect it to AI readiness assessment, so training deals with the systems you actually plan to use. The record gives later reviewers the reason for the decision rather than a collection of unexplained ticks.

People need to know which tools are approved, which information can be entered, who grants access and where to ask when a task falls outside the agreed use. Use a realistic exercise involving a shared document or customer record, and require participants to explain their next action. Use the AI governance framework guide as a working outline and the AI risk assessment guide to practise describing concrete failures, controls and residual uncertainty. Keep those learning exercises distinct from the organisation’s actual authority to accept a risk.

The ICO AI guidance is a source for data-protection considerations and is currently under review. Check current advice with your responsible specialist. This workshop teaches decisions and escalation; it does not determine the legal position of an individual deployment. Extend the exercise through enterprise AI training when multiple departments share a system.

Give participants a reusable use-case record, approval checklist and incident exercise. Nominate someone to maintain them and schedule a review against actual usage. A new model, new information source or wider audience may change the assumptions behind an earlier approval; a policy document alone, even one built from an AI policy template, will not reveal that.

Assess learning by asking participants to explain a decision and demonstrate the next step. Use AI training for business to carry the same boundaries into everyday work, and AI transformation consulting when ownership crosses several functions. Agree follow-up work from the evidence gathered, without treating attendance as proof that risk has been resolved.