Mode: Self-Paced E-Learning
Faculty: Dr. David Peterson, Assistant Professor, Purdue University

This foundational module simplifies complex AI concepts for business leaders and explores the broader social, economic, and ethical implications of artificial intelligence. You’ll gain a clear, non-technical understanding of how AI and deep learning work, why these technologies matter, and what risks they pose—from speculative threats like autonomous weapons to more immediate concerns like algorithmic bias, job displacement, and data privacy.

1. Explain the evolution of AI and deep learning in layman’s terms
2. Analyze the real-world societal and economic risks of AI
3. Critically reflect on ethical dilemmas and AI accountability

   
   

Key Topics:

1. History of Artificial Intelligence
   
2. Deep Learning 101
   
3. Myths vs. Reality: The Singularity and Beyond
   
4. AI’s Risks to Jobs, Markets, and Democracy
   
5. Societal Impacts and Ethics in AI Deployment

Mode: Live Zoom Sessions (8 Sessions)
Faculty: Mr. Kelvin Wu, AI Strategy Consultant & Certified Generative AI Professional

This module helps senior leaders move from understanding AI to applying it strategically. Participants will explore real business use cases for generative AI across industries, assess tools such as ChatGPT and OpenAI, and consider how AI can be embedded within organisational workflows. Ethical concerns and leadership challenges—including data misuse, trust, and workforce disruption—will be addressed through practical frameworks and case studies.

Learning Outcomes:

1. Identify business-relevant use cases for generative AI
2. Evaluate and integrate AI tools within your functional area
3. Lead with ethical awareness and responsible AI principles

Key Topics:

1. Business Applications of Generative AI
2. Strategic Use of AI for Innovation, Customer Experience, and Operations
3. Leadership in an AI-Enabled Organisation
4. Managing Change and AI Transformation
5. Ethical Decision-Making in AI Adoption

Mode: Live Zoom Sessions (8 Sessions)
Faculty: Mr. Kelvin Wu, AI Strategy Consultant & Certified Generative AI Professional

This practical module equips you to define, plan, and lead AI initiatives from concept to execution. You’ll learn how to scope high-impact AI projects, build multidisciplinary teams, secure stakeholder buy-in, and deploy resources efficiently. With tools for planning, risk management, and success measurement, this module is ideal for leaders who need to bring AI strategies to life across departments or business units.

Learning Outcomes:

1. Create a strategic roadmap for enterprise-level AI initiatives
2. Align AI projects with business priorities and performance KPIs
3. Manage the people, data, and change elements in AI implementation

Key Topics:

1. Scoping AI Projects for Business Value
2. AI Roadmap Planning Tools and Milestones
3. Building & Leading Cross-Functional AI Teams
4. Stakeholder Alignment & Resource Allocation
5. Measuring Impact and Communicating Results

Mode: Self-Paced E-Learning
Faculty: Professor Swati Srivastava, Associate Professor & Faculty Scholar, Purdue University

This module explores the global legal, regulatory, and ethical frameworks shaping AI development and deployment. Participants will gain insight into international efforts to regulate AI, including the European Union’s AI Act, soft regulation through industry-led standards, and national approaches to algorithmic transparency and digital sovereignty. Designed for strategic decision-makers, the module helps you assess compliance risks, anticipate regulatory shifts, and build AI governance frameworks.

Learning Outcomes:

1. Analyze the growing international push for AI regulation
2. Identify core issues addressed by global frameworks
3. Understand how to integrate AI governance into corporate policy

Key Topics:

1. Global Trends in AI Regulation
2. Hard vs. Soft Regulatory Approaches (EU, U.S., China, etc.)
3. Digital Sovereignty and Algorithmic Accountability
4. AI Auditing, Transparency, and Ethics-by-Design
5. Future Regulatory Landscapes and What They Mean for Business

This capstone project challenges you to develop a comprehensive AI Project Roadmap and Execution Plan tailored to a real or simulated business environment. Participants will apply the tools, frameworks, and insights gained throughout the module to conceptualize and articulate a detailed strategy for planning and implementing an AI initiative that delivers measurable business value.

This applied assignment is designed to mirror real-world executive planning processes, enabling you to demonstrate your ability to scope projects, engage stakeholders, align with KPIs, and deploy resources effectively. Emphasis will be placed on responsible AI leadership, practical feasibility, and the alignment of AI initiatives with long-term organisational goals.