Overview
Every leader is now expected to have a view on AI, but most of what leaders hear about it comes from vendors selling something or headlines chasing attention. The hard part is not learning the vocabulary; it is building an accurate mental model of what AI genuinely does well, where it fails, and what that means for your business, so you can make decisions without depending on someone else's hype or someone else's fear.
This is a hands-on, foundation course. It assumes no technical background and deliberately covers less ground than a survey course, going deeper on the fundamentals that actually change how you lead: what AI is, what generative AI changes, where value really comes from, and how to judge risk and readiness. The gradient runs from understanding the technology in plain language, to seeing where it creates value, to acting on it as a leader. Every module includes a hands-on lab and builds on the one before.
Who Should Attend
- Business leaders and senior managers who need a working understanding of AI
- Directors and department heads facing AI decisions in budgets, vendors, or hiring
- Professionals moving into roles where AI fluency is now expected
Leaders who already have this grounding and want to build a company-level plan should look at AI Strategy for Executives.
Prerequisites
- None. No technical background is assumed
- Familiarity with your own organization's operations is helpful for the labs
What You Will Learn
- Explain what AI, machine learning, and generative AI are, in plain language and without hype
- Describe what generative AI does well, where it fails, and why
- Identify where AI can create real value in your own business area
- Judge AI proposals and vendor claims with a clear set of questions
- Assess the main risks of AI use and know when to say no
- Build a concrete personal action plan for leading with AI
Course Outline
Day one: what AI actually is and what it can do
- What AI Actually Is
- AI, machine learning, and generative AI: what the terms mean and how they relate
- How models learn, in plain language: patterns, data, and prediction
- A leader's mental model: what is genuinely new and what is rebranded
- Lab: sort a set of real products and headlines by what kind of AI they actually use
- What Generative AI Changes
- What these systems can do today: writing, analysis, images, and conversation
- Strengths and honest limits, including hallucination and inconsistency
- Lab: work hands-on with an AI assistant on real leadership tasks and log where it shines and where it fails
- Where AI Creates Business Value
- The main value patterns: cost, speed, quality, and new capability
- Buying, building, or using AI already embedded in your existing tools
- Separating durable value from pilot-stage hype
- Lab: map three concrete AI opportunities in your own business area
Day two: judging, deciding, and leading
- Risks, Limits, and Responsible Use
- Data privacy, bias, and hallucination as business risks, not just technical ones
- Use cases where AI is the wrong answer
- What responsible use looks like day to day, with a pointer to Responsible AI and AI Ethics for depth
- Lab: evaluate a proposed AI use case against a plain-language risk checklist
- People, Roles, and Adoption
- What AI changes about jobs: tasks change before roles do
- Common reactions on teams, from fear to overuse, and how leaders respond
- Lab: draft a one-page message to your team about how AI will and will not be used
- From Understanding to Action
- The questions to ask about any AI proposal or vendor claim
- What good first steps look like, and what stalls them
- Lab: build a personal 90-day action plan and present it to the group
Extended Version
The three-day version keeps the same gradient and adds depth where leaders ask for it:
- A deeper hands-on day with AI assistants applied to each attendee's real work
- More case studies of AI value and AI failure across industries
- A fuller treatment of readiness: data, talent, and organizational culture
- A capstone in which each leader builds and defends a complete AI briefing for their own organization