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, 296 Seiten, Format (B × H): 152 mm x 229 mm

This is not a book about how to build artifical intelligence (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, nontechnical but mathematically correct explanations, this 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. This 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, In Business with AI 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

In business with AI xx

How to read this book? xxi

From theory to code to boardroom accountability xxxii

How I wrote this book? xxxii

A note on hype, fear, and realism xxxiii

1. What AI is (and what it is not)?

2. A brief history of AI - and why expectations matter

3. How machines learn

4. Key machine learning paradigms

5. Representational foundation of modern AI

6. Generative AI and large language models

7. Neural networks and deep learning

8. Data is the real bottleneck

9. Preparing businesses for AI intregration

In conclusion: AI as normal but complex managerial technology

Acronyms and abbreviations

AI glossary

About the author

Acknowledgments

Index

Über Autor(innen)

Wolfgang Messner is 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.