AI Workshop
LIVE INSTRUCTOR-LED
AI Governance for Leaders
Turn responsible AI principles into practical governance, decision rights and controls that enable innovation without losing oversight.
Design a proportionate AI governance model that connects principles, risk, accountability and delivery.
4 hours Team Workshop Activities and Re-usable content Certificate of participation
Workshop Overview
Overview
AI governance is often discussed as a set of principles, but leaders need practical ways to decide who is accountable, which use cases require deeper review, what evidence is needed and how controls fit into delivery.
AI Governance for Leaders is a practical workshop for business and technology leaders responsible for adopting AI safely and at scale. It translates responsible AI concepts into an operating approach covering roles, risk classification, lifecycle controls, human oversight, third-party considerations and escalation.
Participants leave with a clearer governance model that can support innovation while making accountability and risk decisions visible.
Key Outcomes
By the end of this workshop, you'll be able to:
Explain the core purpose and components of effective AI governance.
Distinguish principles, policies, standards, controls and evidence.
Identify key AI risk areas across data, privacy, security, fairness, transparency, reliability and human oversight.
Classify AI use cases using a proportionate risk-based approach.
Define governance roles, accountabilities and decision rights across business, technology, risk and compliance.
Map governance controls across the AI lifecycle from idea to operation.
Identify when human review, escalation or specialist assurance is needed.
Consider third-party and vendor AI risks.
Create practical governance artefacts that teams can use during delivery.
Balance appropriate oversight with speed of experimentation and adoption.
Workshop Agenda
Explore the workshop
1 Why AI Governance Matters
Explore the leadership decisions governance needs to support.
2 Responsible AI in Practice
Translate high-level principles into operational expectations.
3 AI Risk Landscape
Review common risk categories and how they vary by use case and context.
4 Risk Classification
Create a proportionate way to determine review depth and control requirements.
5 Roles and Decision Rights
Clarify accountability across business owners, technology, data, security, legal, risk and compliance.
6 Lifecycle Governance
Map controls from ideation and design through testing, deployment, monitoring and retirement.
7 Human Oversight and Evidence
Define approval points, required evidence and escalation paths.
8 Third-Party AI
Consider due diligence, contractual and monitoring questions for external solutions.
9 Governance Action Plan
Identify priority gaps and next steps for the organisation.
Who It's For
Built for people doing the work
Executives and senior leaders
AI transformation leaders
Business and functional leaders
CIO, CTO, CDO and technology leaders
Risk and compliance leaders
Data and AI leaders
Product and innovation leaders
Transformation and governance professionals
Hands-on Activities
Learn by doing
Practical exercises you'll complete during the workshop.
Use-case risk classification
Governance RACI exercise
Lifecycle control mapping
Human oversight decision exercise
Third-party AI checklist
Governance gap assessment
Leadership action plan
You'll Leave With
Practical assets you can reuse
AI Governance Operating Model Canvas
AI Risk Classification Template
Governance RACI
AI Lifecycle Control Map
Human Oversight Checklist
Third-Party AI Review Checklist
Governance Gap Assessment
Leadership Action Plan
Certification
Certificate of completion
Certificate of participation is included with this workshop.
Instructor
Meet your instructor
Rajiv Goel
AI Transformation Leader and Microsoft Certified Trainer
AI transformation and enterprise technology leader with extensive experience in AI adoption, business operations, change management and professional training.
FAQs
Common questions
Is this a legal or regulatory training course?
No. It is a leadership workshop on practical AI governance and does not replace legal, regulatory or compliance advice.
Do participants need technical AI knowledge?
No. The focus is on governance decisions, accountability and organisational controls.
Does the workshop cover generative AI?
Yes. Generative AI is included alongside broader AI use cases.
Will we discuss AI regulation?
Relevant regulatory themes can be discussed, but the workshop focuses on building a durable governance approach rather than interpreting law for a specific organisation.
Is the workshop only for risk teams?
No. Effective AI governance requires shared ownership across business, technology, data, risk, security, legal and compliance.
Can we use our existing policies?
Yes. Existing policies and governance artefacts can be used as inputs to the exercises.
How do you avoid creating excessive bureaucracy?
The workshop emphasises proportionate, risk-based governance and clear decision rights.
Can this be customised?
Yes. Exercises can be tailored to your industry, risk appetite, operating model and AI portfolio.
