AI Training

AI Legal Training Overview Participants leave with reviewed legal-work drafts and a repeatable process for using AI as structured support under professional judgement. Who should attend AI Legal is for in-house lawyers, legal counsel, contract managers and other legal professionals who draft, review, research or explain legal matters. Participants should have completed AI Mastery or demonstrate equivalent skill in E-RCFC, variables, prompt chains, model selection and safe AI use.

AI Mastery Training Overview Participants turn one-off prompting into reusable, controlled work and leave with a safe, reviewable next use case. Who should attend AI Mastery is for knowledge workers who have completed AI Fundamentals, or can already use RCFC/E-RCFC, basic model selection and safe AI practices. Participants learn to turn one-off prompting into reusable, controlled work: create useful variation, derive a reusable prompt from a reference, manage variables and context in a prompt chain, compare options against explicit criteria, and choose a safe next use case.

Build practical AI knowledge and skills across your organization with training designed for your teams, leaders, and business context. Our programmes help people understand how to apply AI responsibly, identify valuable use cases, and use AI effectively in their daily work.

Build Your AI Agents Training Overview Participants create reviewed, controlled workflow-change proposals from a non-production workflow. Who should attend Citizen developers, automation builders, business-system analysts and workflow owners use an approved non-production workflow to create a reviewed workflow-change specification, sandbox revision, controlled test record and evidence-based repair proposal. AI assists with low-code workflow drafting and troubleshooting; workflow owners retain architecture, credentials, execution, security, release and production-change decisions.

Design Your AI Agents Training Overview Participants can identify opportunities, frame a bounded automation, score it from explicit assumptions, select a safe prototype scope and define its owner, reviewer, data boundary and success measure.

Hospitality AI Leadership Training Overview Participants create reviewed hospitality AI work using synthetic/approved context: service and staff communication drafts, operational improvement ideas, prioritised use cases and a governed pilot brief. Hospitality, privacy, brand, safety and operations owners retain all decisions.