AI VALUE PLAYBOOK how to make AI work in the real world / Lisa Weaver-Lambert.
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....
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Full Text (via O'Reilly/Safari) |
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| Format: | eBook |
| Language: | English |
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Birmingham, UK :
Packt Publishing Ltd.,
2024.
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| 520 | |a 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 Description 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. 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 for The 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. | ||
| 505 | 0 | |a Cover -- Title Page -- Endorsement -- Copyright and Credits -- Chapter 1: Introduction -- Chapter 2: Overview of AI Concepts and Technology Stack -- Chapter 3: Sam Liang -- CEO of Otter.ai -- Chapter 4: Amr Awadallah -- Founder and CEO at Vectara -- Chapter 5: Philipp Heltewig -- Co-Founder and CEO at Cognigy -- Chapter 6: Miao Song -- Chief Information Officer at GLP -- Chapter 7: Ruben Ortega -- General Partner at Enjoy the Work -- Chapter 8: Joshua Rubin -- Principal AI Scientist at Fiddler AI -- Chapter 9: Nadine Thomson -- Global Chief Technology Officer at GroupM (WPP) | |
| 505 | 8 | |a Chapter 10: Sarvarth Misra -- Co-Founder and CEO of ContractPodAi -- Chapter 11: Edward Fine -- AI and Data Science Consultant, Technologist, and Instructor -- Chapter 12: Sanjeevan Bala -- Group Chief Data and AI Officer at ITV -- Chapter 13: Nathalie Gaveau -- AI Tech Entrepreneur and Board Member -- Chapter 14: Phil Harvey -- Applied AI Architect -- Chapter 15: Elizabeth Ajayi -- Director, Intelligent Industry at Capgemini Invent -- Chapter 16: Louis DiCesari -- Head of Data, Analytics and AI at Levi Strauss & Co. -- Chapter 17: Vickey Rodrigues | |
| 505 | 8 | |a CTO/CDO in Insuretech, Payments, and Healthtech -- Chapter 18: Sean McDonald -- Former Global Chief Innovation Officer at McCann Worldgroup -- Chapter 19: Julie Gray -- Head of Data and Internal Systems at Agilio -- Chapter 20: Peter Jackson -- Chief Data and Technology Officer at Outra -- Chapter 21: Mark Beckwith -- Director of Data Governance and Architecture at the Financial Times -- Chapter 22: Kshira Saagar -- Data Science at Wolt and Doordash -- Chapter 23: Joe Romata -- Global Head of Customer Experience at a multinational energy company -- Chapter 24: Tomasz Ullman | |
| 505 | 8 | |a Former Global Head of Data Science and Strategy at Ford Pro -- Chapter 25: Oz Krakowski -- Chief Business Development Officer at Deepdub -- Chapter 26: LLMs and RAG Enable Hyper-Personalized Education for Healthcare Technicians -- Chapter 27: AI Personalization Increases Engagement in Nascent Tech Communities -- Chapter 28: AI-Powered Virtual Agent Augments Service Efficiency -- Chapter 29: Generative AI Creates a Paradigm Shift in Innovation Processes -- Chapter 30: Unlocking Profit Potential -- Leveraging Enterprise Data for Customer Profitability | |
| 505 | 8 | |a Chapter 31: Minimizing Customer Churn with AI -- Chapter 32: Enhancing Marketing Strategies Through the Power of LLMs -- Chapter 33: Multimodal LLMs Redefine Software Development and Customer Innovation -- Chapter 34: Where We've Got To and What's Next | |
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| 650 | 0 | |a Artificial intelligence. | |
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