Executive AI Governance and Systems Leadership: A Training Course for Senior Managers
1Summary
When an AI system fails at the executive level, it is rarely a coding problem — it is usually a governance gap: no clear ownership of privacy risk, no architecture review process, no one who understood both the technical design and the regulatory exposure. This training course targets senior leaders who carry that responsibility, covering the technical design, data governance, privacy law, and leadership skills needed to make sound strategic calls as AI regulation and technology keep shifting.
Delivered by the Arab British Fellowship Training Academy, the programme builds a working understanding of AI architecture within a global business context, so participants can translate technical decisions into business value rather than leaving them entirely to technical teams.
Core areas covered include:
- Structures for strategic AI management
- Executive-level privacy and compliance oversight
- Key technical architecture decisions
- Running digital transformation plans
- Applying effective governance systems
2Objectives and target group
Who Should Attend?
- IT Directors and Enterprise Architects
- Digital Transformation Leaders
- Data Protection Officers and Privacy Directors
- Compliance Officers and Legal Directors
- Information Security and Risk Management Leaders
In this course attendees will be able to:
- Design efficient implementation plans for data governance and AI systems, using real case studies to ground the ideas in practice.
- Master strategic decision-making in AI governance by examining regulatory frameworks, privacy requirements, and technical architecture across Middle Eastern and international markets.
- Lead institutional transformation and manage risk through recognised compliance frameworks — including PDPL, SAMA guidelines, and EU AI laws — while building governance systems that support both innovation and regulation.
- Connect data privacy, system architecture, and organisational needs into one integrated framework that supports effective leadership of cross-functional teams.
- Build and execute sustainable AI plans grounded in evolving technology, confirmed regulatory requirements, and proven implementation approaches.
3Course Content
Module 1: Privacy Frameworks and Data Foundations
- Global Privacy Framework
- Regional Focus
- Data Classification Systems
- Data Lifecycle Management
- Data Governance Operating Models
Module 2: Assessing and Protecting Data
- Privacy Impact Assessments
- Privacy Risk Assessment Models
- Data Protection Impact Assessments
- Data Anonymization Techniques
- Encryption Standards
Module 3: Embedding Governance and Preparing for What's Next
- Organizational Integration and Privacy Governance Structure
- Privacy Metrics Development and Incident Response
- Emerging Topics in Privacy
- Privacy-Preserving AI Techniques and Federated Learning
Module 4: AI Architecture Foundations and Regional Policy
- Enterprise AI Architecture Patterns
- Cloud vs On-Premise AI Infrastructure
- Saudi Cloud First Policy (verified)
- UAE TRA's actual published guidelines
Module 5: Core Architecture Building Blocks and Oversight
- Model Development Platforms and Data Pipeline Architecture
- API Management and Microservices Architecture
- Architecture Review Boards and Change Management Processes
- Performance Monitoring and Capacity Planning
Module 6: Delivery, Testing and Emerging Architecture
- Continuous Integration/Deployment
- A/B Testing Frameworks and Testing Strategies
- Performance Testing
- Emerging Trends: Edge AI Architecture and Federated Learning Systems