Generative AI Business Applications: An Executive Guide with Real-Life Examples and Case Studies

By David E Sweenor and Yves Mulkers

Within the past year, generative AI has broken barriers and transformed how we think about what computers are truly capable of. But, with the marketing hype and generative AI washing of content, it's increasingly difficult for business leaders and practitioners to go be

• Language: English
• Publisher: TinyTechMedia LLC
• Release date: Jan 31, 2024
• ISBN: 9798989337866

Book preview

Generative AI Business Applications: An Executive Guide

with Real-Life Examples and Case Studies

by David E. Sweenor and Yves Mulkers

Published By:

TinyTechMedia LLC

Copyright © 2024 TinyTechMedia LLC, South Burlington, VT.

All rights reserved.

No part of this publication may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, electronic, mechanical, photocopying, recording, scanning, or otherwise, except as permitted under Sections 107 or 108 of the 1976 United States Copyright Act, without the prior written permission of the Publisher. Requests to the Publisher for permission should be addressed to .

Every effort has been made in the preparation of this book to ensure the accuracy of the information presented. However, the information in this book is sold without warranty, either express or implied. Neither the authors, nor TinyTechMedia LLC, nor its dealers and distributors, will be held liable for any damages caused or alleged to have been caused directly or indirectly by this book. TinyTechGuides is a trademark or registered trademark of TinyTechMedia LLC

Editor: Peter Letzelter-Smith

Cover Designer: Josipa Ćaran Šafradin

Proofreader / Indexer: Peter Letzelter-Smith

Typesetter / Layout: Ravi Ramgati

February 2024: First Edition

Revision History for the First Edition

2024-02-03: First Release

ISBN: 979-8-9893378-5-9 (paperback)

ISBN: 979-8-9893378-6-6 (eBook)

www.TinyTechGuides.com

In Praise Of

Sanjeev Mohan, Founder and

Principal Analyst, SanjMo

Writing a book on AI is like bottling a tsunami. Yet, Yves Mulkers and David Sweenor have managed to compile a tremendous amount of knowledge in this book. I am impressed by the breadth of business use cases as well as their insights into implementation details and governance aspects. This book is bound to spark creative juices and help organizations embark on their AI journey. 

Eric Kavanagh, AI Analyst and Syndicated Radio Host

A Dynamic Duo! Yves Mulkers and David Sweenor have combined forces to create a succinct, compelling explanation of how generative AI can be applied in the real world. From LLMs to CLMs, from guidance to governance, they tackle every relevant aspect of turning AI dreams into business successes. This is a must-read for serious AI executives.

Hyoun Park, Chief Analyst, Amalgam Insights

Every executive needs to read this guide and understand how generative AI is already affecting their business environment! What I love most about this TinyTechGuide is that it provides both industry and departmental examples (over 70). This quick read distills lessons from all of these examples, adds the most salient industry and technology trends, and provides discrete and actionable steps that executives can take this year, this quarter, and this month to make their generative AI efforts more meaningful and business-oriented.

Arup Das, Professor, Applied AI ML, Villanova University

Generative AI has become a pivotal topic in the business world, capturing the attention of CEOs and industry leaders eager to leverage its potential for enhancing productivity, efficiency, and innovation. Yet, the challenge lies in pinpointing the most effective business use cases where Generative AI can drive value creation. This book excels in thoroughly exploring, articulating, and cataloging various business applications across various industries and functional areas. It offers clear, concise examples of diverse business scenarios, making it an indispensable resource for practitioners embarking on their journey with Generative AI.

Tim King, Executive Editor, Solutions Review

Generative AI Business Applications: An Executive Guide to Real-Life Examples and Case Studies is a must-read for leaders looking to realize the full potential of AI in their organizations. Featuring more than just practical advice and best practices, this TinyTechGuide includes sections on implementation and tips for piloting GenAI, a guide to ensuring success in your specific industry or department, and even a deep-dive on key considerations like governance, risk, and compliance. All combined, this is perhaps the most actionable resource that exists on the topic today.

Dedication

Dedication from Dave

To my fabulous family–Erin, Andy, and Chris–thanks for always believing. To Mom and Dad, for your support. To Eric and Laura, for being there. To my friends, colleagues, co-workers, and network, for your support and advocacy of TinyTechGuides.

Dedication from Yves

To my wonderful wife, Liesbeth, who lets me walk my path. To my fabulous kids, that walk their own paths, and show life is amazing to live. To all the wonderful peers and experts who acknowledge and appreciate my vision, insights, and knowledge. To my breakthrough coach who helped me find (back) my passion, self-belief, and my self-worth. To my dog, that reminds me to get away from the laptop and go for a walk. To all my friends, who pull me out of my tech zone.

Prologue

TinyTechGuides are designed for practitioners, business leaders, and executives who never seem to have enough time to learn about the latest technology and marketing trends. These guides are meant to be read in an hour or two and focus on the application of technologies in a business, government, or educational setting.

After reading this guide, we hope that you’ll have a better understanding of how generative AI can be applied in the real world—as well as a better idea of how to use best practices in your business or organization.

Wherever possible, we share practical advice and lessons learned over our careers so you can take our learning and transform it into action.

Remember, it’s not the tech that’s tiny, just the book!™

If you’re interested in writing a TinyTechGuide, please visit www.tinytechguides.com.

Table of Contents

Chapter 1

A New Era of AI

What is Generative AI?

Types of Generative AI Models

Getting Your Data Into the Model

State of the Industry

Practical Advice and Next Steps

Summary

Chapter 1 References:

Chapter 2

Generative AI Across Industries

Banking and Finance

Energy and Utilities

Government and Public Sector

Healthcare

Insurance

Legal

Life Sciences

Manufacturing

Media and Entertainment

Retail

Telecommunications

Transportation and Logistics

Practical Advice and Next Steps

Summary

Chapter 2 References:

Chapter 3

Generative AI Across Departments

Business Operations

Finance

Human Resources

Information Technology

Education and Skill Development

Legal

Procurement

Research and Development

Sales and Marketing

Service and Support

Supply Chain

Practical Advice and Next Steps

Summary

Chapter 3 References

Chapter 4

Implementation

Major Components of Gen AI Tech

Practical Advice and Next Steps

Summary

Chapter 4 References:

Chapter 5

Governance, Risk, and Compliance

AI Ethics

AI Guardrails

Accuracy and Reliability

Cost Considerations

Data Privacy

Data Security

Fairness and Bias

Interpretability and Explainability

Organizational Impact

Privacy

Regulatory Concerns

Safety and Security

Skills

Society and Environmental Impact

Technical Complexity

Transparency and Accountability

Practical Advice and Next Steps

Summary

Chapter 5 References:

Chapter 6

Getting Started with Generative AI

The Business Case

People and Processes

Technology Considerations

Practical Advice and Next Steps

Summary

Chapter 6 References:

Acknowledgments

About the Authors

Chapter 1

A New Era of AI

What is Generative AI?

In the summer of 1956, when computers were still novel, a small team of researchers gathered on the prototypical New England college campus of Dartmouth College to discuss artificial intelligence (AI).¹ Since this seminal gathering, we’ve dreamed about the promise of artificial general intelligence (AGI). Popular culture—from Star Trek to Star Wars—embraced its potential while the actual tech stayed out of our reach down here on plain old planet Earth.

Fast forward to November 2022. The generative AI application ChatGPT took the world by surprise. For those who’ve been stranded on a remote desert island, ChatGPT is an AI-powered chatbot created by OpenAI. Just five days after launch, ChatGPT had garnered more than a million active users and over 100 million users two months later.²,³ For comparison, to amass that many users TikTok took 9 months, Instagram 2.5 years, and Facebook 4.5 years.⁴ According to the latest figures, ChatGPT has around 1.7 billion users worldwide—that’s quite impressive.

What’s the appeal? Generative AI has broken barriers and transformed what we think computers are truly capable of. Everyone now has the potential to create text, code, images, audio, and video that is nearly indistinguishable from human-generated content. Using nothing more than an Internet browser and the innate ability to ask questions—known as prompts—creativity is no longer bounded by innate skills.

Unlike traditional AI, which deals primarily with numeric data and occasionally small amounts of text, generative AI refers to AI systems capable of