AI for Business

AI for Business

Building Applications using Python

Edition 1.0 | Copyright 2027 | Publication Date: June 2026

Tingting (Rachel) Chung, William & Mary
Steven Hojnicki, William & Mary

Overview


AI is transforming all aspects of business and indeed life in general. Students are increasingly using AI in their personal and academic lives. However, most do not know how AI works. For them, AI is a magic box. Some business students will seek to become AI product leads, consultants, or managers, and will need a more rigorous understanding.

AI for Business demystifies AI. Students gain genuine insight into the design and use of AI algorithms (especially deep learning) by developing progressively more involved models using the TensorFlow library in Python to solve a wide range of business problems. A prior programming class, statistics class, and high school math will prove highly useful. A review of the essential Python and mathematical foundations used is provided.

Features


Generate powerful insights into AI
End-of-chapter programming exercises provide direct experience in the design, training (data provided), and use of AI algorithms which creates grounded scientifically-accurate understanding.

Engage students
Concepts are presented slowly, playful examples are provided, and a series of worksheets provide hands on activities. 

Contextualize learning
Each chapter opens with a mini-case that explores the business needs for the features discussed in the chapter.

Advance critical thinking
Through direct experience students learn to evaluate claims about AI products, assess model reliability, and determine when to incorporate human judgement.

Emphasize responsible use
Ethics in Action boxes throughout the text introduce concerns and include questions to ponder. The final chapter explores ethics, responsibility and risk. After learning to develop, train, and use AI models, students bring greater perspective to pondering these concerns.

Testimonials


“It’s almost impossible to find an AI book for business students that can balance the technical and business cases. ‘AI for Business’ is the only book that I have seen that is written specifically for business students.”
–- Mark Pisano, Southern Connecticut State University


“‘AI for Business’ makes the content so much more approachable for business students without compromising technical rigor, from the questions and visual guides that are pedagogically effective to the conversational tone and relatable analogies (including banking, sports rankings) to introduce otherwise abstract ideas.”
-– Yuan (Lucy) Zhang, Auburn University


 “The presentation, sequencing, clear writing, and the online materials that support the content of ‘AI for Business’ make me want to teach my course using this book.”
-– Brian Rudolph, Iowa State


 

Table of Contents


Detailed Table of Contents PDF

Chapter 1: What is AI?
Chapter 2: Programming Tools for Deep Learning
Chapter 3: Mathematical Foundations of AI Models
Chapter 4: Estimating Values
Chapter 5: Making Categorical Decisions
Chapter 6: Evaluating and Improving Model Performance
Chapter 7: Inner Workings of Deep Learning (DL) Model Training
Chapter 8: Visual Intelligence
Chapter 9: Language - Embeddings and LSTM
Chapter 10: Large Language Models
Chapter 11: Recommenders
Chapter 12: Ethics, Responsibility, and Risks

About the Authors


Rachel (Tingting) Chung is a Clinical Full Professor of Operations and Information Systems at College of William & Mary. She loves teaching AI and data analytics using fun activities and props including sticky notes, chocolate, and her children’s book AI The Magic Box: An Activity Book on Artificial Intelligence. She has created AI and data inspired poetry, music, and co-designed data inspired stickers and jewelry. She has received four Faculty Excellence Awards.

In addition to academic research and teaching, Dr. Chung is also very involved in the applying scientific research methods to solve business problems. She has led teams of business students on over twenty client projects with executives from City of Pittsburgh, WQED, AllFacilities Energy Group, Ardex Americas, TingWall, Coca Cola, and others. She is a also a Volunteer Portfolio Project Manager with AI4ALL, a nationwide nonprofit that prepares undergraduates from historically excluded backgrounds for careers in AI.

In 2019, Dr. Chung served on the Advisory Board of the NSF-funded project on Big Data Education at Penn State University, and co-hosted the 3rd Data Science Educator Workshop. That same year, Dr. Chung received the Community Partner of the Year Award from Houston Methodist Hospital on behalf of INFORMS. She earned her Ph.D. in Business Administration/Management Information Systems from the University of Pittsburgh in 2009.

Tingting (Rachel) Chung

Steven Hojnicki is a section lead for College of William & Mary’s Online MBA and MSBA programs. He is also an active-duty officer in the United States Army. He specializes in operations research and systems analysis.

In addition to his military service and teaching responsibilities, he holds key staff positions with two veteran-oriented non-profits. He serves as the Director of MBA Operations for Service to School, which provides free college application counseling; and as Chief Analytics Officer for Hero Hut, which supports veterans in finding creative outlets for community service.

Steven Hojnicki

Instructor Resources


Prospect Press provides instructors with an instructor manual, lecture slides and a test bank for each title. Some texts have additional resources including case teaching notes, tutorials, and addenda.

This content is available to instructors only and is password protected.

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