<p>A practical, non-technical program that builds true AI and data literacy: what AI is (and is not), how data is collected and monetized, where analytics creates value, how to reason about risk using simple statistics, and how to make informed and ethical decisions. Participants complete the program with a clear framework of value, ethics, and empowerment.</p><h3><strong>Objectives</strong></h3><p><strong>Explain</strong> what AI is, where it appears in everyday life, and how it differs from traditional analytics.</p><p><strong>Identify</strong> common data sources (including IoT, data brokers, and synthetic data) and articulate basic privacy risks and protections.</p><p><strong>Differentiate</strong> between BI (Business Intelligence) and Data Science, and describe the 4-level analytics/AI maturity journey (reporting → autonomy).</p><p><strong>Apply</strong> simple decision-making tools (decision matrix, Pugh matrix, OODA loop) to choose with greater clarity and confidence.</p><p><strong>Interpret</strong> basic prediction concepts (probability, variation, confidence, confusion matrix, false positives/negatives) for risk-aware decision-making.</p><p><strong>Map</strong> value beyond money (customers, employees, environment, society) and connect it to AI use cases.</p><p><strong>Develop</strong> a simple “AI and Data Citizen” action plan for one’s role or team.</p>