AI Governance and Ethics

This course contains the use of artificial intelligence. AI tools are used in the production of this course, including AI-assisted speech delivery based on the instructor’s own voice. All content, demonstrations and materials have been personally designed, reviewed, and verified by the instructor to ensure accuracy and practical value.

AI has stopped being a project run by a specialist team down the corridor. It is now a tool on every desk — drafting, analysing, summarising and, increasingly, taking action on its own. Most organisations are still trying to govern it with frameworks designed for something else entirely.

This course shows you how to build practical, operational AI governance for the tools your people already use, including ChatGPT, Claude and Microsoft 365 Copilot. You will move from a shared definition of governance through law and standards, data and security, agents and human oversight, and day-to-day enterprise operations, to a prioritised roadmap you can start on this week.

What you will cover:

• Governance fundamentals: what AI governance means in 2026, the current product landscape, core responsible-use principles, the full AI lifecycle, and matching oversight to real risk.
• Law, policy and standards: the EU AI Act, NIST AI RMF, the UK’s regulator-led approach and other regimes, ISO/IEC 42001 and assurance evidence, internal AI policy, procurement and third-party risk.
• Data, security and privacy: data classification and minimisation, prompt injection, leakage and agent overreach, personal data and lawful basis, and content provenance and authenticity.
• Prompting, agents and human oversight: governed prompts and libraries, safe agent boundaries, agent mode in Word, Excel and PowerPoint, APIs and tool calls, and review checkpoint design.
• Generative content and decisions: content and copyright risk, bias testing and recourse, and explainability so that AI supports decisions rather than quietly making them.
• Operating governance in the enterprise: governance structures and roles, use-case intake and approval, controls for everyday workplace AI, and incident management.
• Sector applications: healthcare and life sciences, financial services and insurance, the public sector and education, and professional services.
• Implementation and maturity: assessing where you stand, a prioritised roadmap with meaningful metrics, role-based AI literacy, and preparing for multi-agent systems.

Why this course is different:

• It governs the AI your people actually use today, not only systems built in-house.
• It is practical throughout: governance treated as an operating discipline, not a one-off approval or a policy document that sits on a shelf.
• It sizes oversight to risk, so low-risk use keeps moving while high-stakes decisions get the scrutiny they need.
• No technical or legal background is required.

Who this course is for:

• Risk, compliance, legal and audit professionals responsible for AI oversight
• IT, security and data protection leads rolling out ChatGPT, Claude or Copilot
• Managers and business owners who need to approve, run or answer for AI use in their teams
• Professionals in regulated sectors such as healthcare, financial services, the public sector and education
• Anyone asked to write, implement or refresh their organisation’s AI policy