The British Academy for Training and Development offers Executive Leadership in Artificial Intelligence Systems training course. Training for Executive Leaders in Artificial Intelligence Systems is for senior leaders responsible for dealing with the AI strategy, implementation and governance of the organisation. The programme is designed to learn technical architecture, data governance, privacy regulations and leadership skills in order to equip these leaders with informed strategic decisions in the AI landscape. You will learn the depth and detail of AI in the mind of global business organisations and the required knowledge of an AI architecture for best organisation value extraction.

Key highlights of the Executive Leadership in Artificial Intelligence Systems training course are:

• Developing understanding on a strategic AI governance framework

• Directing internal privacy and compliance initiatives

• Making key decisions on technical architecture

• Driving Digital Transformation Strategies

• Establishing Effective Governance Models

Objective:

By the end of the course attendees will be able to:

• By examining approved legal frameworks, privacy standards, and technological designs throughout the Middle East and world markets, mastering strategic decisionmaking in AI governance allows leaders in digital transformation to be empowered.

• Using real-world case studies, create successful implementation plans for data governance and artificial intelligence systems to guarantee practical application of the knowledge acquired.

• Understand acknowledged compliance frameworks, including PDPL, SAMA guidelines, and EU AI legislation, and create strong governance systems that promote innovation and control by leading organisational transformation and manage risks.

• Understanding the links between data privacy, system design, and business demands helps to create and manage integrated technical and governance systems, therefore guaranteeing effective cross-functional team leadership.

• Knowing developing technologies, approved regulatory needs, and verified implementation techniques will help to create and execute sustainable artificial intelligence plans, therefore developing long-term adoption of AI.

Who Should Attend?

This course is ideal for:

• Directors of IT charged with managing digital transformation and AI strategy need a thorough understanding of technical architecture as well as governance systems.

• Digital Transformation Leaders controlling AI system integration and guaranteeing conformance with regional legislation including SAMA guidelines and PDPL.

• Privacy Directors and Data Protection Officers (DPOs) in charge of upholding data governance systems and making sure AI projects meet regulatory requirements.

• Enterprise Architects and Technical Directors engaged in the design and integration of artificial intelligence systems who must reconcile technical requirements with governance needs.

• Directors and Compliance Officers dealing with risk management and AI-related legislative issues.

• Leaders of risk management and information security assigned to protect artificial intelligence systems and data while making certain compliance with security policies.

• C-suite executives, senior managers, innovation leaders, and lawmakers accountable for strategic decisionmaking and leading technology-driven change in their companies will find this course to be perfect.

How will attendees benefit?

Attendees in the Executive Leadership in Artificial Intelligence (AI) Systems training course for leaders will get a great array of advantages meant to improve their strategic, technical, and ethical leadership skills in the age of AI. Their benefits are as follows:

• Understanding of AI Systems strategically: Attendees will acquire a thorough understanding of machine learning, data governance, and AI system architecture that will let them match their company's long-run plan with artificial intelligence capabilities.

• Improved Decision Making Abilities: Leaders will find in artificial intelligence insights how to make decisions based on data, ethics, and awareness, particularly in challenging or high-stakes situations when human bias or error may affect results.

• Leadership for Change and Innovation: The course offers attendees developing the leadership attitude needed to lead cross-functional teams in tech-driven projects, manage digital transformation efforts, and fuel AI innovation.

• Managing Risk and Artificial Intelligence Ethics: Attendees will know how to evaluate and minimise risks connected with artificial intelligence adoption including ethical issues, prejudice reduction, and regulatory compliance thereby guaranteeing responsible AI leadership.

• Cooperating with Technical Teams: Executives will acquire the conceptual understanding and vocabulary to work effectively with data scientists, engineers, and IT teams, hence enhancing project results and communication efficiency.

• Enhancement in Organisational Influence: Attendees will be prepared to create AI-ready civilisations, digital projects, and encourage innovation inside their companies or teams by using leadership approaches customized to AI surroundings.

• Competitive Edge: Leaders finishing this course will put themselves and their companies at the forefront of digital transformation, hence giving them a strategic advantage in the fast changing technological environment.

Module 1: Data Governance, Privacy & Integrity in Artificial Intelligence (AI)

• Global Privacy Framework

• Regional Focus

• Data Classification Systems

• Data Lifecycle Management

• Data Governance Operating Models

• Privacy Impact Assessments

• Privacy Risk Assessment Models

• Data Protection Impact Assessments

• Data Anonymization Techniques

• Encryption Standards

• Organizational Integration

• Privacy Governance Structure

• Privacy Metrics Development

• Incident Response

• Emerging Topics

• Privacy-Preserving AI Techniques

• Federated Learning

Module 2: Artificial Intelligence Systems Architecture and Governance

• Enterprise AI Architecture Patterns

• Cloud vs On-Premise AI Infrastructure

• Saudi Cloud First Policy (verified)

• UAE TRA's actual published guidelines

• Model Development Platforms

• Data Pipeline Architecture

• API Management

• Microservices Architecture

• Architecture Review Boards

• Change Management Processes

• Performance Monitoring

• Capacity Planning

• Continuous Integration/Deployment

• A/B Testing Frameworks

• Testing Strategies

• Performance Testing

• Emerging Trends

• Edge AI Architecture

• Federated Learning Systems