AI Governance, Risk & EthicsProtect the organisation. Enable the future.
This focused programme gives governance, risk, and compliance professionals the practical tools to assess AI risk, design ethical guardrails, and build governance structures — without needing a technical background in AI.
Certification
AI Governance Practitioner Certificate
Outcomes that change
how you work.
- Conduct an AI risk assessment using a structured, repeatable methodology
- Apply the EU AI Act risk classification framework to existing and proposed AI deployments
- Design an AI ethics policy that is practical, enforceable, and culturally credible
- Build an AI incident response process from detection to remediation to reporting
- Identify and address AI bias in hiring, lending, healthcare, and other high-stakes contexts
- Establish oversight mechanisms for AI systems operating at scale
- Document AI governance for regulatory and audit purposes
- Communicate AI risk and ethics to boards and senior leadership with confidence
Built for specific people.
Risk Managers
Risk professionals responsible for identifying and managing AI-related risks across the enterprise.
Compliance Officers
Compliance professionals ensuring AI adoption meets regulatory requirements and internal standards.
Internal Auditors
Audit professionals who need to audit AI systems and governance frameworks effectively.
Legal & Privacy Teams
Legal and data protection professionals advising on AI-related legal risk and privacy compliance.
Real challenges. Real solutions.
AI risk is not in the risk register
Most enterprise risk frameworks have no specific AI risk taxonomy. As AI deployment scales, this gap creates growing unmanaged exposure.
Ethics principles are not operational
Having an AI ethics statement is very different from having an ethical AI assessment process. This programme builds the operational layer.
Governance teams are not involved in AI decisions
AI deployments are often approved without formal governance review. This programme gives governance teams the tools and language to participate effectively.
Regulators are asking questions organisations can't answer
Regulators increasingly expect formal AI governance documentation. Organisations without it face examination risk.
Practical governance for the AI era.
This programme focuses on the operational aspects of AI governance: how to assess risk, design policy, establish oversight, and document compliance. Every framework and tool is designed for use in real governance and compliance workflows — not as theoretical constructs.
8h
Duration
GRC-Focused
Audience
Audit-Ready
Outputs
What the programme covers.
AI Risk Identification
- AI risk taxonomy: technical, ethical, regulatory, reputational, operational
- Mapping AI risk to your existing enterprise risk framework
- High-risk AI use cases in regulated industries
- AI risk assessment methodology: a step-by-step process
Regulatory Compliance
- EU AI Act: risk categories, requirements, and compliance timeline
- GDPR and AI: data minimisation, purpose limitation, automated decisions
- ISO 42001 overview: what it requires and how to demonstrate alignment
- Sector-specific regulation: Financial Services, Healthcare, Government
AI Ethics in Practice
- Ethics principles to operational policy: bridging the gap
- AI bias: identifying high-risk contexts and mitigation approaches
- Transparency and explainability requirements: when and how
- Stakeholder engagement in AI ethics: employees, customers, regulators
Governance & Oversight Structures
- AI governance committee design and terms of reference
- AI incident response: detection, escalation, investigation, and remediation
- AI audit: scope, methodology, and documentation
- Reporting AI governance performance to boards and regulators
See it applied in the real world.
Risk Manager
Has been asked to include AI risk in the quarterly risk report for the first time. Needs a methodology and a starting set of identified risks.
Uses the programme's AI risk taxonomy and assessment methodology to produce a comprehensive AI risk register in 3 days. Report submitted on time with full governance team confidence.
Compliance Officer
Organisation is deploying an AI-powered customer credit scoring system. Needs a GDPR and EU AI Act compliance review before go-live.
Applies the compliance review framework. Identifies 4 issues requiring remediation before deployment. System launched compliantly, 3 weeks later than originally planned but without regulatory exposure.
Internal Auditor
Annual audit scope has been expanded to include AI systems. Needs an AI audit methodology that can be applied consistently across 12 AI deployments.
Designs an AI audit framework adapted from the programme materials. Completes all 12 audits with a consistent, documented approach. Audit report accepted by Audit Committee without challenge.
Learn by doing, not watching.
Lab 01
AI Risk Assessment Exercise
Apply the risk assessment methodology to a real or simulated AI deployment. Produce a risk register, risk rating, and recommended mitigation actions.
Lab 02
EU AI Act Classification Workshop
Work through the EU AI Act classification decision tree for 5 AI use cases. Produce classification decisions and compliance requirement summaries.
Lab 03
AI Ethics Policy Draft
Draft an AI ethics policy for a specified organisation. Apply peer review and facilitator feedback. Produce a policy ready for stakeholder consultation.
Lab 04
AI Governance Committee Design
Design an AI governance committee for a specified context. Define mandate, membership, decision authority, and operating procedures.
Different by design.
Practical, Not Theoretical
Every session starts with a real business problem. Concepts are introduced only when they serve a specific outcome you need to deliver.
Real Use Case Focus
We teach through scenarios drawn from real professional contexts — Finance, HR, Marketing, Leadership — so learning transfers immediately.
Designed for Simplicity
Complexity is hidden. Clarity is foregrounded. You get exactly what you need to act — without being overwhelmed by what you don't.
Tool Adoption Science
Our methodology is built on behavioural science and habit formation principles — so you actually use what you learn, not just remember it.
Neuroscience Principles
Learning design based on how brains retain and apply information. Spaced repetition, active retrieval, and contextual practice built in.
ISO 42001 Certified
MHCAI is the only AI learning institute that combines ISO 42001 certification, role-specific academies, and a human-centred methodology.
Build AI governance that works in practice.
Available as a standalone workshop for GRC teams or as a module within the AI Governance Academy. Designed for governance professionals, not technologists.