About This Course
Artificial intelligence is reshaping industries at an unprecedented pace, bringing with it a new class of risks that traditional risk management and compliance frameworks were never designed to address. From algorithmic bias and data privacy breaches to opaque decision-making systems and cross-border regulatory conflicts, organisations that deploy AI without a structured governance approach face serious legal, reputational, and operational exposure.
The global regulatory landscape for AI is maturing rapidly. The European Union AI Act — the world's first comprehensive AI law — is now in force, while jurisdictions across Africa, the Middle East, and beyond are issuing AI strategies, guidelines, and binding regulations at speed. Risk, compliance, legal, and technology leaders must urgently build the competencies to interpret these frameworks, assess their organisation's AI risk posture, and implement proportionate controls.
TrainingComplex's AI Risk Management and Regulatory Compliance Training is a rigorous five-day programme that translates complex AI governance concepts into actionable professional practice. Participants will gain a thorough grounding in AI risk typologies, global and regional regulatory requirements, ethical AI principles, audit and assurance approaches, and the practical mechanics of embedding compliance into AI procurement, development, and deployment lifecycles.
The programme draws on real-world case studies, regulatory texts, and hands-on risk assessment exercises to ensure that learning translates directly to participants' working environments. Whether your organisation is building AI systems, procuring them from vendors, or simply making decisions informed by AI outputs, this training provides the governance foundation you need to operate with confidence and accountability.
Who Should Attend
- Risk and Compliance Officers responsible for AI-related governance and oversight
- Legal Counsel and Regulatory Affairs professionals advising on AI adoption
- Chief Data Officers, AI Product Managers, and Technology Leaders
- Internal Auditors and Assurance professionals reviewing AI systems
- Procurement and Vendor Management professionals acquiring AI solutions
- Policy and Governance Officers in public sector and regulated industries
- Senior Managers and Executives accountable for AI strategy and ethics
- Data Protection Officers with AI-related privacy responsibilities
Learning Objectives
- Explain the core concepts of artificial intelligence relevant to risk and compliance professionals
- Identify and categorise the principal risk types associated with AI systems, including algorithmic, operational, legal, and reputational risks
- Interpret and apply key global AI regulatory frameworks, including the EU AI Act, GDPR, and emerging African and Middle Eastern AI regulations
- Conduct an AI risk assessment using structured methodologies and risk classification tools
- Design and implement an AI governance framework aligned to organisational risk appetite and regulatory obligations
- Evaluate AI systems for ethical compliance, fairness, transparency, and accountability
- Apply data governance and privacy controls within AI development and deployment pipelines
- Develop AI-specific compliance policies, procedures, and internal controls
- Oversee AI vendor and third-party risk management, including due diligence and contractual protections
- Prepare for AI regulatory audits and build effective AI risk reporting for senior leadership and boards
Course Modules
Module 1: Understanding Artificial Intelligence: A Risk and Compliance Primer
- Key AI concepts: machine learning, deep learning, generative AI, and automation
- How AI systems are trained, validated, and deployed in organisational settings
- Difference between narrow AI, general AI, and large language models in practice
- The AI system lifecycle: design, development, deployment, monitoring, and decommissioning
- Why traditional risk and compliance frameworks are insufficient for AI
- Building AI literacy for non-technical risk and compliance professionals
Module 2: AI Risk Landscape: Typologies and Emerging Threats
- Algorithmic bias and discriminatory outcomes: causes and consequences
- Opacity and explainability failures in AI decision-making
- Data poisoning, adversarial attacks, and cybersecurity risks specific to AI
- Operational risks: automation failures, model drift, and system dependency
- Reputational and ethical risks from irresponsible AI deployment
- Legal liability questions: who is responsible when AI causes harm
Module 3: Global AI Regulatory Frameworks
- The EU AI Act: structure, risk classification tiers, and compliance obligations
- GDPR and automated decision-making: Article 22 and its practical implications
- United States AI executive orders, NIST AI Risk Management Framework, and sector-specific rules
- African Union AI policy landscape and national AI strategies across the continent
- Middle Eastern AI regulatory developments: UAE, Saudi Arabia, and Qatar frameworks
- Principles for navigating multi-jurisdictional AI regulatory obligations
Module 4: AI Risk Classification and Assessment Methodology
- Applying risk-based approaches to AI system classification
- High-risk versus low-risk AI: regulatory thresholds and organisational criteria
- AI-specific risk assessment templates: probability, impact, and controllability dimensions
- Mapping AI risks to existing enterprise risk management frameworks
- Stakeholder analysis: who is affected by AI risk and how
- Documenting and maintaining an AI risk register
Module 5: Ethical AI Principles and Governance Standards
- Core principles of responsible AI: fairness, transparency, accountability, and human oversight
- International ethical AI standards: OECD, UNESCO, and ISO/IEC guidelines
- Embedding ethics into AI project governance gates and approval processes
- AI ethics committees: structure, mandate, and decision-making authority
- Managing tensions between commercial AI objectives and ethical obligations
- Reporting on AI ethics performance to leadership and external stakeholders
Module 6: Data Governance and Privacy in AI Systems
- Data quality, provenance, and bias as foundational AI risk factors
- Lawful basis for processing personal data in AI training and inference
- Data minimisation, purpose limitation, and retention controls for AI datasets
- Privacy impact assessments adapted for AI systems and automated pipelines
- Cross-border data transfer risks in global AI supply chains
- Synthetic data, anonymisation, and privacy-enhancing technologies for AI compliance
Module 7: Designing an AI Governance Framework
- Core components of an organisational AI governance framework
- AI governance roles: AI ethics officer, model risk officer, and responsible AI committee
- Policies and procedures specifically required for AI risk and compliance
- Integrating AI governance into existing corporate governance and risk structures
- Setting and communicating AI risk appetite and tolerance thresholds
- Governance documentation: AI registers, model inventories, and decision logs
Module 8: AI Procurement, Vendor Risk, and Third-Party Compliance
- Risk profile of procured versus internally developed AI systems
- AI-specific due diligence: assessing vendor transparency, explainability, and bias testing
- Key contractual clauses for AI procurement: liability, audit rights, and data ownership
- Managing ongoing third-party AI risk through vendor monitoring programmes
- Regulatory obligations when deploying AI systems developed by third parties
- Exiting AI vendor relationships: data retrieval, system decommissioning, and transition risk
Module 9: AI Audit, Assurance, and Internal Controls
- Internal audit's evolving role in AI governance and oversight
- Designing an AI audit programme: scope, objectives, and testing methodology
- Technical and process controls for AI model validation and performance monitoring
- Conformity assessments and third-party AI certification under the EU AI Act
- Continuous monitoring of AI systems: trigger events and periodic review cycles
- Building audit trails and evidentiary documentation for regulatory inspections
Module 10: AI Compliance Reporting, Incident Response, and Future Readiness
- AI risk reporting frameworks for boards, audit committees, and senior leadership
- Designing AI incident response plans: detection, escalation, and regulatory notification
- Post-incident review and lessons-learned integration into AI governance
- Engaging with regulators: proactive disclosure, regulatory sandboxes, and consultations
- Monitoring regulatory change and maintaining organisational AI compliance readiness
- Building a culture of responsible AI across the organisation through training and accountability
Requirements & Prerequisites
Participants should have a working knowledge of risk management, legal compliance, or technology governance concepts at a professional level. Familiarity with data protection principles or basic regulatory frameworks is beneficial but not mandatory. No prior technical expertise in artificial intelligence or machine learning is required, as the programme provides the necessary AI literacy foundation.
Training Methodology
- Regulatory text analysis workshops where participants dissect and interpret extracts from the EU AI Act, GDPR, and regional AI frameworks
- Structured AI risk assessment exercises using real-world organisational scenarios drawn from finance, healthcare, public sector, and retail
- Case study reviews of high-profile AI failures, regulatory enforcement actions, and governance successes across global industries
- Group deliberation sessions where participants debate AI ethics dilemmas and apply ethical frameworks to contested real-world decisions
- Vendor due diligence simulation in which participants evaluate a fictional AI supplier's documentation, contracts, and compliance claims
- Hands-on development of AI governance artefacts including risk registers, policy templates, and audit checklists tailored to participants' own organisations
- Peer review and critique exercises where small teams assess each other's AI risk assessments for completeness and accuracy
- Expert-facilitated discussion on emerging regulatory trends and how organisations should prepare for forthcoming obligations
Organisational Benefits
- Reduced legal and regulatory exposure from AI deployments through structured compliance controls
- Strengthened organisational governance over AI procurement, development, and operations
- Enhanced ability to respond swiftly and confidently to emerging AI regulations across multiple jurisdictions
- Improved stakeholder and public trust through demonstrable commitment to ethical and responsible AI
- Better-informed board and leadership decision-making on AI investments and risk appetite
- Reduced likelihood of costly AI incidents, enforcement actions, or reputational damage
- A workforce equipped to embed compliance thinking into AI projects from design to deployment
- Competitive advantage through credible AI governance that meets the expectations of clients, partners, and regulators
Where Is AI Risk Management and Regulatory Compliance Training Offered?
This course runs in-person across: Mombasa, Zanzibar, Nairobi, Cape Town, Abuja, Kigali, Riyadh, Nakuru, Dubai, Lagos, Kampala, Addis Ababa, Accra, Naivasha, Pretoria, Arusha, Kisumu, Johannesburg, Dar es Salaam, plus Live Virtual (online) cohorts. Browse live dates for your city below.
Upcoming Schedules
| Location | Format | Dates | Price |
|---|
| Live Virtual |
Online |
12 Oct 2026 – 16 Oct 2026 |
KES 80,000 |
| Live Virtual |
Online |
24 Oct 2026 – 15 Nov 2026 |
KES 80,000 |
| Mombasa, Kenya |
In-Person |
26 Oct 2026 – 30 Oct 2026 |
KES 120,000 |
| Zanzibar, Tanzania |
In-Person |
26 Oct 2026 – 30 Oct 2026 |
USD 2,500 |
| Nairobi, Kenya |
In-Person |
26 Oct 2026 – 30 Oct 2026 |
KES 115,000 |
| Cape Town, South Africa |
In-Person |
26 Oct 2026 – 30 Oct 2026 |
USD 3,800 |
| Abuja, Nigeria |
In-Person |
26 Oct 2026 – 30 Oct 2026 |
USD 2,800 |
| Kigali, Rwanda |
In-Person |
26 Oct 2026 – 30 Oct 2026 |
USD 1,900 |
| Riyadh, Saudi Arabia |
In-Person |
26 Oct 2026 – 30 Oct 2026 |
USD 4,500 |
| Nakuru, Kenya |
In-Person |
26 Oct 2026 – 30 Oct 2026 |
KES 120,000 |
| Dubai, United Arab Emirates |
In-Person |
26 Oct 2026 – 30 Oct 2026 |
USD 4,100 |
| Lagos, Nigeria |
In-Person |
26 Oct 2026 – 30 Oct 2026 |
USD 2,500 |
| Riyadh, Saudi Arabia |
In-Person |
2 Nov 2026 – 6 Nov 2026 |
USD 4,500 |
| Abuja, Nigeria |
In-Person |
2 Nov 2026 – 6 Nov 2026 |
USD 2,800 |
| Kampala, Uganda |
In-Person |
2 Nov 2026 – 6 Nov 2026 |
USD 1,900 |
+228 more dates — view live schedule →
Frequently Asked Questions
Do I need a technical background in AI to attend this course?
No technical background is required. The programme opens with an accessible AI literacy module designed specifically for risk, compliance, and legal professionals. The focus throughout is on governance, regulation, and risk management rather than coding or data science.
Which regulatory frameworks does this course cover?
The course covers the EU AI Act, GDPR automated decision-making provisions, the NIST AI Risk Management Framework, and a range of emerging African and Middle Eastern AI regulations. It is designed to give participants a multi-jurisdictional perspective applicable to international organisations.
Will I receive a certificate upon completion?
Yes. Participants who attend the full five-day programme and complete all practical exercises will receive a TrainingComplex Certificate of Completion in AI Risk Management and Regulatory Compliance, which can be used for professional development records and CPD purposes.
Is this course suitable for public sector organisations?
Absolutely. The course includes case studies and examples drawn from both private sector and public sector contexts, covering health, financial services, and government. Regulated-industry professionals will find the content directly applicable to their operating environment.
Can this training be delivered in-house for our organisation?
Yes. TrainingComplex offers customised in-house delivery of this programme, tailored to your organisation's specific AI systems, regulatory jurisdiction, and internal governance structures. Contact TrainingComplex directly to discuss a bespoke engagement.
