EMBA 8160: Artificial Intelligence for Leaders

Listen to the introduction

Transcript

Speaker	Text
Alex	This is the brief on the artificial intelligence for leaders course. Think of this comprehensive 6 session playbook as exactly what you need as a busy executive to go from basic AI curiosity to successfully leading your company’s AI transformation. First, how did we actually get from simple chatbots to systems that run entire workflows? Well, it’s the jump from basic generative AI to agentic AI systems. You can think about it like this. Basic gen AI is kind of like a smart intern who needs constant instructions, while agentic AI acts as an autonomous project manager that connects to your data, plans steps, and takes independent action toward a goal. Second, we look at strategically applying this tech in marketing, customer service, and product development to drive real revenue. You’ll get a clear build or buy framework for choosing your solutions. But look, I really have to push back on the hype here. These tools are absolutely not just plug and play. Without embedding proper data feedback loops into your enterprise systems so they can learn from their mistakes, that shiny new tool is going to stagnate quickly. Finally, we zero in on the guardrails you absolutely need to protect your business. We dive into ethics, managing bias, preventing AI hallucinations, you know, where the system just confidently makes things up, and in navigating strict data privacy laws. Seriously, what good is a powerful AI system if it breaks privacy regulations or your team is too intimidated to even use it? That’s why cross-functional teams and change management are so critical to get organizational buy-in. Ultimately, this course provides the strategic foundation you need to stop merely talking about AI and start confidently leading real AI integration.

Speaker

Text

Alex

This is the brief on the artificial intelligence for leaders course. Think of this comprehensive 6 session playbook as exactly what you need as a busy executive to go from basic AI curiosity to successfully leading your company’s AI transformation. First, how did we actually get from simple chatbots to systems that run entire workflows? Well, it’s the jump from basic generative AI to agentic AI systems. You can think about it like this. Basic gen AI is kind of like a smart intern who needs constant instructions, while agentic AI acts as an autonomous project manager that connects to your data, plans steps, and takes independent action toward a goal. Second, we look at strategically applying this tech in marketing, customer service, and product development to drive real revenue. You’ll get a clear build or buy framework for choosing your solutions. But look, I really have to push back on the hype here. These tools are absolutely not just plug and play. Without embedding proper data feedback loops into your enterprise systems so they can learn from their mistakes, that shiny new tool is going to stagnate quickly. Finally, we zero in on the guardrails you absolutely need to protect your business. We dive into ethics, managing bias, preventing AI hallucinations, you know, where the system just confidently makes things up, and in navigating strict data privacy laws. Seriously, what good is a powerful AI system if it breaks privacy regulations or your team is too intimidated to even use it? That’s why cross-functional teams and change management are so critical to get organizational buy-in. Ultimately, this course provides the strategic foundation you need to stop merely talking about AI and start confidently leading real AI integration.

The objective of this course is to prepare participants with a solid understanding of Generative AI’s transformative potential and its implications for shaping the future of business and society.

This course offers an immersive introduction to Generative Artificial Intelligence (AI) and its implications for modern businesses. Participants will delve into the historical context and fundamental concepts of (Generative) AI, exploring its evolution and impact on various industries. Through interactive discussions, case studies, and hands-on activities, students will gain a comprehensive understanding of key concepts such as neural networks, generative models, and the practical applications of transfer learning and prompt engineering.

Throughout the course, participants will explore the diverse applications of Generative AI, including creative content generation, natural language processing, and healthcare advancements, while analyzing real-world case studies to understand implementation challenges and ethical considerations. Engaging in group activities and discussions, students will refine their problem-solving skills, foster collaboration, and explore strategies for integrating Generative AI into existing business frameworks. Additionally, discussions on ethical practices and responsible AI will underscore the importance of transparency and fairness in AI-driven decision-making processes.

Schedule

Class Schedule
Session	Date	Topic	In Class	Project Milestone
1	2026-09-18	Intro Generative AI	Lecture, Activity, Reflection
2	2026-09-19	Agentic AI Systems	Lecture, Hands-on Exercise
3	2026-10-03	Strategic Applications of Generative AI in Business	Team Activity & Presentation	AI System Project progress report
4	2026-10-17	Operationalizing Generative AI – Integration and Customization	Quiz 1, Team Activity & Presentation
5	2026-10-31	Risk Management and Ethical Considerations in Generative AI	Quiz 2, Team Activity & Presentation
6	2026-11-07	Leading Generative AI Transformation in Organizations	Quiz 3, Team Activity & Presentation	AI System Project deployment on server

Documents

Course Syllabus (PDF)

Learning Objectives

Upon successful completion of this course, students will gain “Ready for work” skills, including:

Understand the historical context and fundamental concepts of Generative AI.
Build AI systems.
Explore applications of Generative AI across industries, including creative content generation, natural language processing, and healthcare.
Analyze real-world case studies to understand implementation challenges and ethical considerations.
Refine problem-solving skills and foster collaboration through group activities and discussions.
Develop strategies for integrating Generative AI into existing business frameworks responsibly and ethically.

Topics

Project

The semester project is to design and build a Study Buddy: an agentic AI learning partner that helps you prepare for class, test your understanding, apply course ideas to your own work, and improve over time. You build it in your own n8n environment using LLMs, web search, document storage, and a vector database, and you develop it across four reviews that carry increasing weight toward your project grade. The project rewards the quality of your learning design, the clarity of your workflow architecture, the strength of your prompts, and the evidence that you tested and improved the system, more than it rewards decorative complexity.

Project Milestones

Project Milestones
Milestone	Due
AI System Project: progress report (in class)	2026-10-03
AI System Project: deployment on server	2026-11-07