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Full Description
Learn from real-world examples how leveraging AI, including machine learning and generative AI, is imperative for businesses to navigate risk, drive value, and gain a competitive advantage
Key Features
Understand machine learning and generative AI terminology, concepts, and the AI technology stack.
Learn from diverse real-world case studies narrated by business leaders in their own voice.
Apply a value-driven approach to AI applications across multiple business sectors.
Book DescriptionBusiness 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.What you will learn
Fundamentals of AI concepts and the tech stack
How AI works with real-world practical applications
How to integrate into your company's overall strategy
How to incorporate generative AI in your processes
How to drive value with sector-wide examples
How to organize an AI-driven operating model
How to use AI for competitive advantage
The dos and don'ts of AI application
Who this book is forThe AI Value Playbook is aimed at supporting non-technical executives and board members to quickly formulate a perspective on how to integrate AI. This book addresses the gap in data and AI knowledge in leadership teams that have an appetite for nuanced, targeted and practical solutions. It includes which levers and processes to consider to future-proof their business. It speaks to an audience interested in understanding how AI can drive value for their organisations.
Contents
Table of Contents
Introduction
Overview of AI Concepts and Technology Stack
Sam Liang, CEO of Otter.ai
Amr Awadallah, Founder and CEO at Vectara
Philipp Heltewig, Co-Founder and CEO at Cognigy
Miao Song, Chief Information O
Ruben Ortega, General Partner at Enjoy the Work
Joshua Rubin, Principal AI Scientist at Fiddler AI
Nadine Thomson, Global Chief Technology O
Sarvarth Misra, Co-Founder and CEO of ContractPodAi
Edward Fine, AI and Data Science Consultant, Technologist, and Instructor
Sanjeevan Bala, Group Chief Data and AI O
Nathalie Gaveau, AI Tech Entrepreneur and Board Member
Phil Harvey, Applied AI Architect
Elizabeth Ajayi, Director, Intelligent Industry at Capgemini Invent
Louis DiCesari, Head of Data, Analytics and AI at Levi Strauss & Co.
Vickey Rodrigues, CTO/CDO in Insuretech, Payments, and Healthtech
Sean McDonald, Former Global Chief Innovation Officer at McCann Worldgroup
Julie Gray, Head of Data and Internal Systems at Agilio
Peter Jackson, Chief Data and Technology O
Mark Beckwith, Director of Data Governance and Architecture at the Financial Times
Kshira Saagar, Data Science at Wolt and Doordash
Joe Romata, Global Head of Customer Experience at a Multinational Energy Company
Tomasz Ullman Former Global Head of Data Science and Strategy at Ford Pro
Oz Krakowski Chief Business Development O
Case Study: LLMs and RAG Enable Hyper-Personalized Education for Healthcare Technicians
Case Study: AI Personalization Increases Engagement in Nascent Tech Communities
Case Study: AI-Powered Virtual Agent Augments Service Efficiency
Case Study: Generative AI Creates a Paradigm Shift in Innovation Processes
Case Study: Unlocking Profit Potential - Leveraging Enterprise Data for Customer Profitability
Case Study: Minimizing Customer Churn with AI
Case Study: Enhancing Marketing Strategies Through the Power of LLMs
Case Study: Multimodal LLMs Redefine Software Development and Customer Innovation
Where We've Got To and What's Next
