AI Foundations and the Landscape
Tell predictive, generative, and agentic AI apart and know what each is good for. Place the current moment in its historical arc, and read the landscape of model providers and tool categories as it actually stands.
Mastering AI for Business
Eight modules over eight weeks, online and self-paced. You start with a clear map of what AI is and finish with a written playbook for putting it to work in your own organization. Launching spring 2027.
Why this course
Most executive AI programs pick one of two altitudes. They teach you the tools, and you leave able to write a better prompt but no clearer about where AI belongs in your business. Or they stay strategic, and you leave with a point of view you cannot act on. This course runs both, in sequence, over eight weeks, because the two questions answer each other.
An earlier version of this program ran with international cohorts through 2025. I have rebuilt it for the University of Miami Business School: the content is current, agents are treated as the center of gravity rather than a closing footnote, and the whole thing now builds toward one artifact you keep.
What you will learn
- Read the current AI landscape and tell predictive, generative, and agentic AI apart.
- Judge where AI creates durable economic value and where it is a feature anyone can buy.
- Use generative AI well in your own creative and knowledge work.
- Decide which work to delegate to an agent, and what to do when it gets things wrong.
- Lead people through AI change without dismissing what they are worried about.
- Leave with a written AI playbook for your own organization.
The eight modules
One module a week. Each opens with a business problem, works through the frame and the evidence, asks you to apply it to your own situation, and ends with a knowledge check.
AI Economics and Strategy
Where AI creates economic value, and why some firms compound an advantage while others spend a great deal and get little. The three engines behind a durable edge (learning curves, network effects, the data flywheel), and the build, buy, or partner call.
Using Generative AI: Creativity, Learning, and Work
The hands-on module. The practical toolkit, a prompting method that holds up under real work, and using AI to sharpen your own creative and knowledge output and to learn faster.
AI Automation and Agents
The shift from prompting to delegating. Augmentation, automation, and agentic execution, what agents can and cannot do today, and how to re-architect a piece of knowledge work so people and AI each do what they are better at.
Algorithmic Management and AI Leadership
What changes when AI is no longer the thing you use but the thing that directs, evaluates, and coordinates the work. Autonomy and control, trust, psychological safety, and what has to stay human. Anchored in my own field research inside a financial services firm.
Building a Data-Driven AI Organization
Why proprietary data is the real moat and where retrieval fits. How to place your organization on an adoption-maturity curve honestly, and what moves a firm from scattered pilots to scale. Worked through CEMEX and DBS Bank.
Responsible, Trustworthy, and Sustainable AI
Responsible AI as a set of practices rather than a values statement. The governance landscape (the EU AI Act, the NIST AI Risk Management Framework, UNESCO, OECD), how it connects to cybersecurity and sustainability, and how to build it into the lifecycle so it survives contact with real deadlines.
Emotional Intelligence and Leading Through AI Change
The capstone. The hardest part of AI at work is rarely the technology. Reading how people actually respond to new tools, answering resistance without dismissing it, communicating change in a way that lowers fear, and closing your playbook.
What you leave with
An AI playbook for your own organization. Each module writes one section of it, so the work you do during the course accumulates into a single document rather than a folder of notes. By Module 8 it is an operating manual you can hand to your team: where AI creates value in your business, which work you are delegating, how you are governing it, and how you plan to bring people with you.
Who it is for
Leaders, managers, and professionals who need to use AI well and judge where it belongs in their organization. No technical background is assumed and there is no coding. It suits people who are past the demo stage and are being asked what to actually do.
Practical details
- Online, self-paced
- Eight modules, one per week
- Eight weeks
- Spring 2027
- To be announced
- To be announced
- None. No technical background required.
- Certificate of completion, University of Miami
Register your interest
Enrollment opens in spring 2027. Register your interest now and the University of Miami Business School Executive Education team will contact you with dates and pricing as soon as they are set. For questions about the content, or whether the course fits you or your team, write to me directly.