-
Book Overview & Buying
-
Table Of Contents
The AI Value Playbook
By :
The AI Value Playbook
By:
Overview of this book
Business leaders are challenged by the speed of AI innovation and how to navigate disruption and uncertainty. This book is a crucial resource for those who want to understand how to leverage AI to drive business value, drawn from the firsthand experience of those who have been implementing this technology successfully.
The AI Value Playbook focuses on questions frequently posed by leaders and boards. How can businesses adapt to these emerging technologies? How can they start building and deploying AI as a strategic asset to drive efficiency? What risks or threats need to be considered? How quickly can value be created?
This book is a response to those demands. In a series of in-depth and wide-ranging conversations with practitioners, from CEOs leading new generative AI-based companies to Data Scientists and CFOs working in more traditional companies. Our experts share their hard-earned wisdom, talking candidly about their successes and failures, and what excites them about the future. These interviews offer unique insights for business leaders to apply to their own organizations. The book distils a value-driven playbook for how AI can be put to work today.
Table of Contents (43 chapters)
Free Chapter
In Praise of The AI Value Playbook
Chapter 1: Introduction
Chapter 2: Overview of AI Concepts and Technology Stack
Chapter 3: Sam Liang
Chapter 4: Amr Awadallah
Chapter 5: Philipp Heltewig
Chapter 6: Miao Song
Chapter 7: Ruben Ortega
Chapter 8: Joshua Rubin
Chapter 9: Nadine Thomson
Chapter 10: Sarvarth Misra
Chapter 11: Edward Fine
Chapter 12: Sanjeevan Bala
Chapter 13: Nathalie Gaveau
Chapter 14: Phil Harvey
Chapter 15: Elizabeth Ajayi
Chapter 16: Louis DiCesari
Chapter 17: Vickey Rodrigues
Chapter 18: Sean McDonald
Chapter 19: Julie Gray
Chapter 20: Peter Jackson
Chapter 21: Mark Beckwith
Chapter 22: Kshira Saagar
Chapter 23: Joe Romata
Chapter 24: Tomasz Ullman
Chapter 25: Oz Krakowski
Case Study
Chapter 26: LLMs and RAG Enable Hyper-Personalized Education for Healthcare Technicians
Case Study
Chapter 27: AI Personalization Increases Engagement in Nascent Tech Communities
Case Study
Chapter 28: AI-Powered Virtual Agent Augments Service Efficiency
Case Study
Chapter 29: Generative AI Creates a Paradigm Shift in Innovation Processes
Case Study
Chapter 30: Unlocking Profit Potential – Leveraging Enterprise Data for Customer Profitability
Case Study
Chapter 31: Minimizing Customer Churn with AI
Case Study
Chapter 32: Enhancing Marketing Strategies Through the Power of LLMs
Case Study
Chapter 33: Multimodal LLMs Redefine Software Development and Customer Innovation
Chapter 34: Where We’ve Got To and What’s Next
