In Business with AI

What Leaders Must Understand Before Deploying Artificial Intelligence at Scale
1. Auflage 2026
ISBN: 978-1-041-35378-2
Verlag: Taylor & Francis Ltd

Buch, Englisch, 230 Seiten, Format (B × H): 152 mm x 229 mm

This is not a book about how to build AI. It is a book about what leaders must understand before deploying AI.

This comprehensive guide demystifies AI concepts, explores its history, and empowers readers to navigate its impact on business and society. Grounded in clear, non-technical but mathematically correct explanations, the book explores AI from foundational principles to advanced topics including neural networks and machine learning paradigms. Readers will gain a deeper understanding of how AI systems work, their limitations, and practical strategies for leveraging AI responsibly. The book highlights that AI systems are not built by algorithms alone, but by organizations that choose objectives, learning paradigms, data, thresholds, and incentives—choices that sit squarely with leadership. With its expert analysis and real-world advice, the book bridges the gap between technical knowledge and managerial decision-making, equipping leaders to make those choices confidently and correctly.

Ideal for business leaders seeking to understand and apply AI concepts, this book is also a valuable resource for professionals, educators, and students who want to enhance their knowledge of AI's role in shaping the future.

Zielgruppe

Adult education, Postgraduate, and Professional Practice & Development

Autoren/Hrsg.

Messner, Wolfgang

Fachgebiete

• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz
• Wirtschaftswissenschaften Betriebswirtschaft Bereichsspezifisches Management Management: Führung & Motivation

Inhaltsverzeichnis

List of Figures. List of Info Boxes. Journey Through the Book. Prologue: Why This is not a Technical Book. Chapter 1: What AI is (and What it is not). Chapter 2: A Brief History of AI – and why Expectations Matter. Chapter 3: How Machines Learn. Chapter 4: Key Machine Learning Paradigms. Chapter 5: Representational Foundation of Modern AI. Chapter 6: Generative AI and Large Language Models. Chapter 7: Neural Networks and Deep Learning. Chapter 8: Data as the Real Bottleneck. Chapter 9: Preparing Businesses for AI Integration. In Conclusion: AI as Normal but Complex Managerial Technology. Acronyms and Abbreviations. AI Glossary. About the Author. Acknowledgements

Über Autor(innen)

Wolfgang Messner is a Clinical Professor at the Darla Moore School of Business, University of South Carolina. His work focuses on how artificial intelligence methods can be used and governed for business applications.