An Interactive 10-Day Training Course

Executive Leadership in Artificial Intelligence (AI) Systems

Mastering Data Governance, Privacy, and Technical Architecture

30 Nov - 11 Dec 2026
Dubai
| $11900

Introduction

This Executive leadership in Artificial Intelligence (AI) systems training course designed for senior leaders responsible for organizational AI strategy, implementation, and governance. The training course combines technical architecture, data governance, and privacy frameworks with leadership and strategic decision-making. You gain a better understanding of AI in a global business context and important additional knowledge of AI architecture requirements maximise value.

The following are the highlights of this GLOMACS Executive Leadership in Artificial Intelligence (AI) Systems training course:

Key Learning Outcomes

The primary objectives of the training course is to help delegates to:

Training Methodology

Participants will increase competencies through a variety of instructional methods including lecture, exercises, reviewing published articles, checklists, videos, and group discussions. A comprehensive training course manual enabling practical application and reinforcement is provided.Delegates are encouraged to bring real problem examples with them, for discussion on a confidential basis, and to share their experience of particular issues

Executive Leadership in Artificial Intelligence (AI) Systems

Who Should Attend?

The organization will benefit by:

  • Establishing robust, compliant AI governance frameworks aligned with verified regional regulations
  • Creating integrated data governance and technical architectures based on proven implementations from leading organizations, ensuring efficient resource utilization and improved operational performance
  • Developing sustainable compliance processes that adapt to changing regulatory requirements, supported by documented frameworks and implementation methodologies from successful regional digital transformation initiatives
  • Building stronger cross-functional collaboration between technical and governance teams through shared understanding of verified frameworks, improving project execution and reducing implementation risks
  • Enhancing competitive advantage through properly governed AI implementations that balance innovation with compliance, based on documented success cases.

Learning Journey Breakdown

Module I: Data Governance, Privacy & Integrity in Artificial Intelligence (AI)

Global Privacy Framework

  • EU GDPR and AI Systems
  • China's Personal Information Protection Law (PIPL)
  • Saudi Arabia's Personal Data Protection Law (PDPL)
  • UAE Federal Decree Law No. 45 of 2021
  • African Data Protection Harmonization Framework

Regional Focus

  • SAMA Data Privacy Guidelines
  • Qatar Financial Centre Privacy Rules
  • African Regional Frameworks
  • Privacy implementation in AI systems
  • Cross-border data transfer solutions
  • Compliance monitoring systems

Core Components

  • Data Classification Systems
  • Data Lifecycle Management
  • Privacy by Design Principles
  • Data Quality Management

Implementation

  • Data Governance Operating Models
  • Privacy Impact Assessments
  • Data Protection Controls
  • Monitoring Systems

Risk Framework

  • Privacy Risk Assessment Models
  • Data Protection Impact Assessments
  • Vendor Risk Management
  • Cross-border Data Transfers 

Technical Controls

  • Data Anonymization Techniques
  • Encryption Standards
  • Access Control Systems
  • Audit Mechanisms
  • Risk assessment methodology
  • Technical controls implementation
  • Compliance monitoring
  • Organizational Integration
  • Privacy Governance Structure
  • Role Definition and Responsibilities
  • Training and Awareness
  • Change Management

 Monitoring

  • Privacy Metrics Development
  • Incident Response
  • Reporting Frameworks
  • Continuous Improvement
  • Emerging Topics
  • Privacy-Preserving AI Techniques
  • Federated Learning
  • Synthetic Data
  • Edge Computing Privacy

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