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. Participants practise four connected legal workflows in AIM: controlled contract drafting, contract review and negotiation, client communication, and legal research. They leave with reviewed draft outputs and a repeatable process for using AI as structured support—not as legal advice, legal authority or a replacement for professional judgement.

AI Mastery Training Overview Participants turn one-off prompting into reusable, controlled work and leave with a safe, reviewable next use case. Prompts are can be shared with colleagues and other departments for company-wide adoption and efficiency.

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 Roles: Citizen developers, automation builders, business-system analysts and workflow owners. Prerequisites: Foundation training in AI or daily practice validated by AI Maturity Assessment. Participants bring knowledge of their organisation, market, department and workflows. Platform access: Either an internal AI corporate platform with agentic coding capabilities, a Microsoft 365 Copilot corporate license. Alternatively, a temporary AIM platform can be deployed for the training. Delivery context: Facilitated practice-based 3h workshop. This training can have participants from different departments and divisions. Participants must prepare their own sanitized data to test their AI Agent. What you will learn Inspect a sandbox workflow’s trigger, nodes, input/output flow, credentials boundary and execution record. Write a bounded, version-aware workflow modification request with acceptance tests and a rollback point. Review AI-generated workflow. Test expected versus actual behaviour with controlled valid and malformed inputs. Diagnose invalid code, execution errors and wrong behaviour using redacted, reproducible evidence.

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.