Lead genAI adoption: pick use cases, run pilots, manage risk, and scale responsibly
Generative AI is moving fast—and most organizations are reacting in pieces: a few employees experimenting with chat tools, a pilot that never scales, and leadership meetings full of hype but light on clarity. Meanwhile, competitors are using genAI to move faster, serve customers better, and redesign workflows in ways that compound over time.
What you’ll learn
- Explain what generative AI is, how it differs from predictive AI, and what it can reliably do in business contexts..
- Identify high-value genAI use cases by mapping AI capabilities to business goals and workflow friction points..
- Design and launch low-risk pilots with clear success metrics (time saved, quality, CSAT, conversion, cost-to-serve)..
- Implement practical guardrails: human review, source grounding, privacy rules, and escalation paths for sensitive cases..
- Create an adoption plan: training, AI champions, communication, and change management that reduces fear and resistance..
- Choose a build/buy approach and understand when RAG/internal knowledge assistants beat fine-tuning for enterprise needs..
Course Content
- Introduction & Foundations –> 3 lectures • 23min.
- Generative AI Landscape & Trends –> 2 lectures • 18min.
- Applications Across Business Functions –> 4 lectures • 35min.
- Strategy, Ethics, and Case Studies –> 4 lectures • 32min.
Requirements
Generative AI is moving fast—and most organizations are reacting in pieces: a few employees experimenting with chat tools, a pilot that never scales, and leadership meetings full of hype but light on clarity. Meanwhile, competitors are using genAI to move faster, serve customers better, and redesign workflows in ways that compound over time.
And if you’re a leader, the real challenge isn’t “What is ChatGPT?”
It’s: Where do we start? What’s safe? What’s valuable? And how do I bring my team along without creating chaos?
That’s exactly what this course is designed to help you do.
In Generative AI for Leaders, you’ll get a practical, business-first playbook for leading genAI adoption—without needing to become technical. You’ll learn what genAI can (and can’t) do, how it’s already being used across marketing, customer support, operations, HR, finance, and product, and how to turn scattered experimentation into a clear strategy.
You’ll also go deeper than generic “prompt tips” by learning how leaders set guardrails, manage risk, measure ROI, and build a culture that treats AI as an accelerator—not a replacement. And you’ll study a real rollout in a highly regulated environment through a detailed Morgan Stanley case study, showing what it looks like to deploy genAI responsibly at scale.
In this course, you’ll learn how to:
- Understand the genAI landscape (text, images, code, agents) and what’s realistic for your org right now
- Identify high-impact use cases by starting from business goals—not tools
- Run small pilots that actually produce measurable results
- Redesign workflows around AI (not just “add AI” to existing work)
- Set policies for privacy, security, and acceptable use
- Reduce risks like hallucinations, bias, and compliance issues with practical governance
- Build an AI-ready culture through training, champions, and change management
- Decide when to buy vs. build and how retrieval + internal knowledge assistants work in practice
By the end, you won’t just “get” generative AI—you’ll know how to lead with it: making confident decisions, guiding your team through change, and turning AI into durable business advantage.