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Full Description
Actionable Information Enterprises Need to Transform into an AI-Fueled Business
In an era when artificial intelligence is reshaping industries, most organizations still struggle to move beyond experimentation. Enterprise AI Productivity is a timely and authoritative guide that bridges the gap between AI ambition and execution. Written by Selim Mimaroglu, former Director of Data Science and Machine Learning at Oracle, this book offers a structured, experienced roadmap for transforming your organization into a high-performing, AI-powered enterprise.
Think of AI as a dream product--one that requires a symphony of teams, tools, and strategies to bring it to life. While software development has long-established frameworks, AI demands a new organizational blueprint. This book demystifies the complexities of AI adoption by presenting a clear, practical approach to building and scaling AI solutions. Through real-world examples and a chapter-by-chapter breakdown of roles, responsibilities, and workflows, readers will learn how to identify high-impact problems, develop AI models, and deploy them into production with confidence and clarity.
AI Organizational Design: Learn how to structure your teams for success and avoid the pitfalls that cause 80% of AI projects to fail
From Idea to Product: Discover how to move from identifying a business problem to building a scalable AI product family
Model Lifecycle Management: Master the end-to-end process of training, deploying, monitoring, and maintaining AI models
Cross-Functional Collaboration: Understand the roles of individual contributors, teams, and leaders in an AI-driven organization
Real-World Case Studies: Gain insights from the author's hands-on experience leading AI initiatives across global enterprises
Strategic AI Thinking: Explore the differences between product platforms, product families, and industry platforms--and how to leverage each
Contents
Chapter 1: Why AI?
Chapter 2: What Is an AI-Fueled Business?
Chapter 3: How to Structure an AI Organization
Chapter 4: AI Innovation
Chapter 5: AI Product Management
Chapter 6: AI Research
Chapter 7: AI Deployment
Chapter 8: AI Production
Index



