AI did not end the data literacy crisis. It changed it. As machines move from providing information to interpreting it and recommending what to do, the scarce skill is becoming judgment: knowing what to trust, what to question, and what decisions are still ours to make.
Evidence does not make decisions. People interpret it, weigh it, challenge it, and make judgments. A courtroom reveals what leaders can learn about evidence, expertise, confidence, and data-informed decision-making.
Feeling sure doesn't mean you're right. Learn five simple ways to question what feels true, spot what might be influencing you, and make better decisions about what to believe.
Understand, evaluate, and apply AI responsibly, without becoming a technologist. A guided sequence of four journeys that builds practical AI judgment for the people who use AI to make decisions and do better work.
AI is no longer a technical specialty sitting off to one side of the business. It now shapes everyday decisions, workflows, and the way work gets done. This track is built for the professionals on the receiving end of that change: the people who consume AI outputs, weigh AI recommendations, and decide what to do next, but who do not need to build models themselves.
The four journeys move from foundations to judgment. You start with what AI actually is, learn how it works and how it shapes decisions, build the skill of spotting and prioritizing real AI opportunities, and finish with a repeatable way to think critically about any AI output before you act on it.
Status: In development. This track is not open for enrollment yet. The page is published early so you can preview the structure, scope, and learning outcomes. Journey content, links, and progress tracking will go live as each journey is completed.
Recommended approach: Take the journeys in order. Each one assumes the vocabulary and habits of the journey before it, and the track is designed as a single progression from understanding AI to exercising judgment with it.
Each journey is a focused unit with its own assets and outcome. Journeys are not open yet — the cards below preview the planned content and progression.
Replace myths and vague assumptions with an accurate, plain-language understanding of AI: what it is, how it differs from traditional software, the five categories of AI, and how AI literacy extends data literacy.
Look inside the machine. Understand how machine learning is built and trained, where bias and ethical risk enter, and how AI changes decision-making across assisted, augmented, and automated approaches.
Move from understanding AI to applying it. Spot high-value AI opportunities with practical lenses, evaluate ideas with strategic frameworks, and assess whether a use case is genuinely ready for action.
Bring it together into judgment. Use the AI Thinking Loop to question AI outputs, recognize AI's strengths and limits, assess organizational readiness, and practice the responsible habits of an empowered AI consumer.
Understand what AI is, learn how it works and decides, spot where it creates real value, then exercise judgment over every output. Capability builds on capability.
The journeys are in development now. Be the first to know when AI Foundations goes live.
