Foundations of Generative AI is designed specifically for undergraduate business students with no technical background, offering a clear, engaging, and practical introduction to one of today’s most important technologies. Rather than focusing on coding or complex mathematics, the book helps students understand how generative AI works, what it can and cannot do, and how to apply it in real-world business contexts. Core concepts—like tokens, model training, and AI limitations—are explained using intuitive language, real-world examples, and structured, step-by-step learning.

The text emphasizes practical skill-building alongside conceptual understanding. Students learn how to effectively interact with AI tools through prompt engineering, evaluate outputs critically, and apply generative AI across business functions such as marketing, operations, and strategy. At the same time, the book presents a balanced perspective on key issues including bias, ethics, data privacy and security, and workforce disruption—encouraging students to think critically about both the opportunities and risks.

With its student-centered design, each chapter includes clear learning objectives, concise lessons, knowledge checkpoints, and interactive elements that reinforce understanding and engagement. The modular structure makes it easy to integrate into a variety of course formats, while its business-focused approach ensures relevance for today’s workforce. This is not just an introduction to generative AI—it’s a foundation for using it thoughtfully, effectively, and responsibly in a rapidly evolving professional landscape.