Course Details

This course is appropriate for a wide range of professionals but not limited to:

• Business executives, directors, and senior managers
• Strategy, innovation, and transformation leaders
• Department heads (HR, finance, operations, marketing, IT)
• Government and public sector managers overseeing digital initiatives
• Consultants and advisors working on AI and digital transformation

• Expert-led sessions with dynamic visual aids
• Comprehensive course manual to support practical application and reinforcement
• Interactive discussions addressing participants’ real-world projects and challenges
• Insightful case studies and proven best practices to enhance learning

By the end of this course, participants will be able to:

• Understand the fundamentals of AI and its impact on organizations and industries
• Identify high-value AI use cases in business functions and value chains
• Develop strategic roadmaps for AI adoption and innovation
• Address ethical, governance, and change management challenges in AI integration
• Lead cross-functional teams in implementing AI projects responsibly and effectively

DAY 1

AI Fundamentals for Decision Makers

• What is AI? Key concepts: machine learning, NLP, computer vision, automation
• Overview of AI technologies, capabilities, and limitations
• Historical evolution and current trends in AI
• Business value of AI: productivity, personalization, prediction
• Case study

DAY 2

Strategic Applications of AI in the Enterprise

• Identifying business functions ripe for AI disruption (HR, finance, marketing, supply chain)
• Use case analysis: customer service bots, fraud detection, predictive maintenance
• Building vs. buying AI solutions: strategy and cost-benefit analysis
• Integrating AI with existing business models and systems
• Workshop

DAY 3

AI Leadership, Change, and Organizational Readiness

• Leading digital and AI transformation initiatives
• AI talent, skills, and operating models
• Building cross-functional teams and managing change
• KPIs and metrics for evaluating AI impact
• Group activity

DAY 4

Ethical, Legal, and Governance Considerations

• AI ethics: bias, fairness, accountability, transparency
• Regulatory landscape: GDPR, AI Act, and sector-specific guidelines
• Building ethical governance frameworks for AI implementation
• Stakeholder communication and trust-building
• Case study

DAY 5

The Future of Work and Leading with AI

• AI and the future of work: workforce augmentation vs. automation
• The role of AI in sustainability, innovation, and competitive advantage
• Leading continuous AI innovation and creating a learning organization
• Emerging technologies: generative AI, edge AI, and autonomous systems
• Final group project