Faysal AzizEthical AI in Action
Practical governance for business leaders
Review AI risks, governance responsibilities and policy choices through a practical business-focused workshop.
Why this course
This one-day course introduces practical AI governance for business leaders. Participants examine ethical risks, regulatory awareness, oversight roles and evidence that can support decisions about AI use.
A guided chatbot risk assessment and policy-drafting exercise turn the principles into a small, illustrative governance proposal. The course provides an introductory framework for discussion and further review, not a full enterprise implementation, legal opinion or certification.
Learning outcomes
The course teaches participants to:
- Explain fairness, transparency, accountability, privacy, security and human oversight in business AI use.
- Distinguish voluntary governance frameworks from legal requirements and identify where jurisdiction-specific advice is needed.
- Review example model documentation, audit trails and risk assessments.
- Draft selected governance policy clauses and an escalation matrix for an illustrative scenario.
- Outline practical next steps and measures for reviewing an organisation’s AI governance.
Prerequisites
- Basic understanding of AI/ML concepts
- Familiarity with current business processes where AI is applied
No programming or legal qualification is required. The workshop is intended for participants with basic business-process knowledge.
7 modules
011. Why AI Governance Matters3 topics
- Illustrative scenario: an AI service delivers uneven results for different user groups.
- Discuss how missing ownership, documentation or review can undermine trust.
- Assess adoption opportunities and ethical, operational and reputational risks without assuming a financial return.
022. Regulatory Awareness3 topics
- EU AI Act awareness: scope, risk-based requirements and how to check current official implementation information.
- Compare jurisdiction-specific approaches at a high level; distinguish applicable law, policy guidance and international initiatives rather than treating them as universal rules.
- Illustrative financial-services scenario: identify oversight questions for an AI-assisted decision process.
033. Governance Principles and Frameworks3 topics
- Core pillars: explainability, auditability, privacy, fairness, human oversight, sustainability
- Use a transparent workshop risk-assessment template informed by the NIST AI Risk Management Framework; identify the purpose, stakeholders, possible harms and controls.
- ISO/IEC 42001 overview: an AI management-system standard for organisational governance and continual improvement, not a technical model-development recipe.
044. Evidence and Risk-Assessment Tools3 topics
- Review example logging, audit trails, model cards and monitoring indicators, including drift.
- Guided chatbot risk assessment using synthetic information and the workshop template.
- Environmental considerations: energy, water and carbon impacts; recognise the limits of estimates and available measurement data.
055. Roles, Oversight and Escalation3 topics
- Board oversight & ethics councils
- From pilot to enterprise: AI team roles and escalation matrix
- Illustrative professional-services scenario: evaluate AI use, confidentiality and human review without using real client material.
066. Policy-Drafting Workshop3 topics
- Draft selected clauses for an illustrative policy: purpose, risk classification, review frequency, transparency and oversight measures. Flag clauses requiring specialist legal or organisational review.
- Peer review: simulate internal governance review
- Feedback & iteration
077. Governance Roadmap and Review3 topics
- Governance maturity roadmap: quick wins to long-term initiatives
- Training & awareness programs for staff and leadership
- Define review measures such as unresolved risks, documented controls, audit findings and checks against applicable requirements.
A programme built around your team.
Share your training goals and requirements.