Introduction

As artificial intelligence becomes embedded across critical business processes, organisations face growing pressure to govern AI responsibly, transparently, and in line with emerging international standards. Poorly governed AI systems expose organisations to regulatory, ethical, operational, and reputational risks. ISO/IEC 42001 provides a structured management system standard specifically designed to address these challenges by establishing governance, risk management, and accountability for AI systems.

The AI Governance and Risk Management based on ISO/IEC 42001 training course equips professionals with a practical understanding of how to design and implement AI governance frameworks aligned with ISO/IEC 42001 requirements. Participants explore AI risk identification, control mechanisms, governance structures, and compliance considerations across the AI lifecycle. The course emphasises integrating governance into enterprise operations to ensure AI systems are reliable, secure, explainable, and aligned with organisational values and regulatory expectations.

Key focus areas include:

Key Learning Outcomes

At the end of this AI Governance and Risk Management based on ISO/IEC 42001 training course, participants will be able to:

Training Methodology

This AI Governance and Risk Management based on ISO/IEC 42001 training course adopts a structured and application-focused learning approach grounded in real organisational AI challenges. Participants engage with ISO/IEC 42001 frameworks, governance scenarios, case-based discussions, and practical analysis to translate standard requirements into actionable governance practices. Emphasis is placed on risk-informed decision-making, compliance alignment, and leadership accountability.

AI Governance and Risk Management based on ISO/IEC 42001

Who Should Attend?

This AI Governance and Risk Management based on ISO/IEC 42001 training course is ideal for:

  • Governance, risk, and compliance professionals overseeing AI initiatives
  • Technology and data leaders responsible for AI deployment
  • Risk managers and internal audit professionals
  • Information security and AI ethics specialists
  • Legal and regulatory professionals involved in AI oversight
  • Professionals supporting enterprise AI governance and assurance

 

Course Outline

Day 1

AI Systems Foundation

Architectural Fundamentals

  • Enterprise AI Architecture Patterns
  • Cloud vs On-Premise AI Infrastructure
  • Distributed AI Systems
  • Model Operations (MLOps)
  • Infrastructure Security Standards

Regional Implementation

  • Saudi Cloud First Policy (verified)
  • UAE TRA's actual published guidelines
  • Qatar's documented Cloud Policy
  • South Africa's GPC framework
  • Nigeria's Cloud Computing Policy
  • Architecture decisions
  • Implementation challenges
  • Governance framework
Day 2

AI System Components

Core Components 

  • Model Development Platforms
  • Data Pipeline Architecture
  • Model Serving Infrastructure
  • Monitoring Systems
  • Version Control for AI 

Integration 

  • API Management
  • Microservices Architecture
  • Container Orchestration
  • Service Mesh Implementation
  • DevSecOps for AI
  • Dubai Smart City
  • System design
  • Integration approach
  • Performance metrics
Day 3

Governance Framework

Technical Governance

  • Architecture Review Boards
  • Change Management Processes
  • Release Management
  • Configuration Management
  • Security Controls

Operational Controls 

  • Performance Monitoring
  • Capacity Planning
  • Disaster Recovery
  • Incident Management
  • SLA Management
  • Governance structure
  • Control framework
  • Risk management
Day 4

Implementation Strategies

Deployment Models

  • Continuous Integration/Deployment
  • A/B Testing Frameworks
  • Canary Deployments
  • Blue-Green Deployments
  • Shadow Deployments 

Quality Assurance

  • Testing Strategies
  • Performance Testing
  • Security Testing
  • Compliance Validation
  • User Acceptance Testing
  •  Etihad Airways
  • Deployment strategy
  • Testing approach
  • Quality metrics
Day 5

Future Architecture

  • Emerging Trends
  • Edge AI Architecture
  • Federated Learning Systems
  • Neural Architecture Search
  • AutoML Platforms
  • Quantum-Ready Architecture

International Standards & Professional Alignment

Our training courses are aligned with internationally recognised professional standards and frameworks across leadership, strategy, finance, governance, risk, compliance, and audit. By integrating globally trusted models, we ensure learners develop practical, relevant, and industry-recognised capabilities.

Our trainings draw on leading international standards and professional frameworks, including ISO, ISACA, COSO, OECD, IIA, FATF, Basel, IFRS/ISSB, GRI, NIST, CPD, ILM and the OECD AI Principles. This alignment ensures consistency with global best practices across financial management, risk oversight, digital governance, sustainability, and strategic decision-making..

Designed in alignment with globally recognised professional bodies, our courses support continuous professional development, strengthen organisational capability, and provide clear pathways toward professional certifications valued worldwide.

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FAQs

The course focuses on governing AI systems using ISO/IEC 42001 to manage risk, accountability, and compliance. 

Yes. ISO/IEC 42001 alignment and regulatory readiness are core components. 

The course is governance-focused, addressing risk, controls, accountability, and oversight rather than system development. 

Yes. Participants gain insight into governance controls and documentation aligned with ISO/IEC 42001. 

Absolutely. ISO/IEC 42001 applies to any organisation developing, deploying, or managing AI systems. 

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