图书简介
Artificial Intelligence (AI) is a game-changing technology that can bring significant value to businesses of all sizes and industries. Research has shown that companies can achieve up to a 3% increase in profits and provide significant business value by successfully adopting it. In this publication, we bring together three experienced authors with a deep understanding of the AI industry to show how to do it. While many publications focus on one or two aspects of AI from a single perspective, this book is a comprehensive guide that provides readers with a framework to navigate the complexities of AI value creation from different perspectives. We explore the various value drivers and obstacles that come with adopting AI and highlight strategies and tactics that successful AI Achievers have used to drive business growth and create value through AI. Our insights are organized into four parts and fourteen chapters, drawing from our own and the experiences of AI Achievers to provide actionable guidance on creating value with AI. Through real world examples, case studies, and interviews with industry leaders, we identify the best practices and common pitfalls that companies face when implementing AI. Our aim is to equip readers with the knowledge and tools necessary to overcome obstacles and reap the rewards of AI. We examine the challenges from multiple perspectives, including business, technology, data, algorithmics, and psychology. By providing practical examples and case studies, we aim to illustrate our points and offer readers the key capabilities required to foster an environment for successful AI value creation.
Introduction Part One Value Creation Potential 1. The Journey of AI Achievers 2. Three Factors of AI Business Value Creation 3. Four Types of AI Value Creation Part Two Overcoming Value Challenges 4. AI-centric Elements 5. Collecting Valuable Data 6. Creating Actionable Insights 7. Building Stakeholder Trust 8. Managing AIs Decision Making Part Three Enterprise Integration 9. Crafting an AI Strategy 10. Leading successful Projects 11. Cultivating an AI-friendly Culture Part Four Required Capabilities 12. Technology 13. Data Management 14. Talent
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