Driving Digital Transformation through Data and AI: A Practical Guide to Delivering Data Science and Machine Learning Pr

Introduction

In an era where data is the new oil, most Indian businesses still struggle to move beyond small-scale machine learning pilots. While global giants like Netflix and Uber have embedded data science into their very DNA, traditional companies often find themselves stuck in a loop of isolated experiments that never reach production. Driving Digital Transformation through Data and AI by Alexander Borek is the definitive guide for Indian leaders, product managers, and data professionals who want to break free from this cycle. This hardcover volume from Kogan Page offers a practical, no-nonsense roadmap to building data and AI products that truly transform your organisation.

Book Overview

This book is not just another theoretical treatise on artificial intelligence. It is a hands-on, strategic playbook designed for executives and practitioners alike. Alexander Borek draws from his extensive experience to provide a clear framework for scaling machine learning from pilot projects to core business operations. The book covers everything from portfolio strategy and agile processes to data architecture and governance, all tailored for the real-world challenges faced by Indian companies in sectors like insurance, fashion, consumer goods, finance, manufacturing, and automotive. Each chapter is packed with templates, common pitfalls to avoid, and global case studies that make the concepts immediately applicable.

Key Highlights

• Practical templates and checklists that you can implement from day one in your organisation.
• Real-world case studies from industries including insurance, fashion, consumer goods, finance, manufacturing, and automotive.
• Agile delivery frameworks specifically designed for data science and machine learning products.
• Strategies to break organisational silos and foster cross-functional collaboration.
• Focus on data architecture and governance as the foundation for scalable AI.

Inside the Book

Dive deep into the essential components of a successful data and AI transformation. The book begins by helping you define a data and AI portfolio strategy that aligns with your business goals. It then walks you through setting up the right organisational structure and agile processes to deliver machine learning products at scale. You will learn how to advance your data architecture and governance frameworks, balance the often conflicting needs of stakeholders, and break down the silos that hinder innovation. Every chapter is designed to be immediately actionable, with templates and checklists that you can adapt to your own context.

Key Topics

• Data and AI portfolio strategy for traditional businesses
• Organisational setup for machine learning product teams
• Agile processes for data science and AI delivery
• Data architecture and governance at scale
• Stakeholder management and breaking silos
• Case studies from insurance, fashion, consumer goods, finance, manufacturing, and automotive

Reader Benefits

By reading this book, you will gain the confidence to lead digital transformation initiatives in your organisation. You will understand how to move from proof-of-concept projects to full-scale production systems that deliver real business value. The practical tools and frameworks will help you avoid common pitfalls that derail AI projects. Indian readers, especially those in fast-growing sectors like fintech, manufacturing, and retail, will find the case studies particularly relevant. This book empowers you to become a change agent who can bridge the gap between business strategy and technical execution.

Learning Outcomes

• Develop a clear data and AI portfolio strategy that drives competitive advantage.
• Design an organisational structure that supports scalable machine learning delivery.
• Implement agile processes tailored for data science and AI product teams.
• Establish robust data architecture and governance frameworks.
• Navigate stakeholder expectations and break down departmental silos.
• Learn from global case studies to avoid costly mistakes.

Who Should Read

This book is ideal for C-suite executives, chief data officers, heads of digital transformation, product managers, data science leaders, and IT professionals who are responsible for driving AI initiatives in their organisations. It is also highly valuable for MBA students and engineering graduates in India who aspire to lead data-driven businesses. If you are a consultant, entrepreneur, or anyone involved in scaling machine learning products, this book is your essential companion.

About the Author

Alexander Borek is a recognised thought leader in data and AI strategy. He has worked with leading global organisations to help them harness the power of data science and machine learning at scale. His practical, no-nonsense approach has made him a sought-after advisor and speaker in the field of digital transformation. Borek’s deep understanding of both the technical and organisational challenges of AI adoption shines through in every chapter.

About the Publisher

Kogan Page is a leading independent publisher of business and professional books. With a strong focus on practical knowledge and real-world application, Kogan Page has been helping professionals and organisations succeed for decades. Their titles are known for their actionable insights and rigorous research, making them a trusted source for business leaders worldwide.

Conclusion

Driving Digital Transformation through Data and AI is more than a book—it is a strategic toolkit for any Indian organisation ready to embrace the future. Whether you are a startup founder in Bengaluru, a product manager in Mumbai, or a data science lead in Pune, this book will equip you with the frameworks and confidence to deliver machine learning products that truly matter. Stop dreaming about digital transformation and start driving it with this essential guide.