Preface

We are at the forefront of a new digital frontier, one in which automation is no longer limited to monotonous activities but rather transforms into a dynamic, intelligent, and strategic enabler of corporate transformation. This transition is represented by Hyper Automation, which combines Robotic Process Automation (RPA), Artificial Intelligence (AI), Machine Learning (ML), Natural Language Processing (NLP), and advanced analytics to reinvent how businesses function, make decisions, and thrive.

Implementing Hyper Automation: Strategies, Best Practices, and Case Studies was formed out of a desire to shed light on this transforming path. This edited collection weaves together a rich tapestry of thought leadership, research, and real-world insights to explain Hyper Automation and its far-reaching impact on industries and institutions.

The book encompasses fourteen chapters, which provide a methodically organized investigation of core principles, strategic frameworks, enabling technology, and implementation best practices. The first five chapters establish a solid foundation by discussing the core, scope, and architectural intricacies of Hyper Automation. These are followed by industry-specific case studies (Chapters 6-10) that explore its implementation in banking, manufacturing, healthcare, and agriculture, demonstrating how theory translates into significant, measurable change. The ensuing chapters (11-12) focus on critical areas of data governance, security, and operational issues, while Chapter 13 looks ahead to upcoming technologies. The final chapter offers a thoughtful perspective on maintaining momentum and encouraging ongoing progress through automation.

What distinguishes this assortment is not just the variety of topics covered, but also the level of competence behind each chapter. The contributing authors are eminent academicians, researchers and professionals who have enhanced this book with scholarly rigor and practical knowledge. Their contributions demonstrate a shared commitment to promoting innovation, bridging the gap between academics and industry, and furthering the conversation on intelligent automation.

This book aims to serve as a compass for students, educators, researchers, practitioners, and policymakers alike, anyone looking to comprehend, implement, or strategize for a future in which automation is more than simply a tool, but a mindset.

We extend our heartfelt gratitude to all contributors and supporters who brought this vision to life. May this work ignite curiosity, provoke thought, and empower its readers to shape a smarter, more adaptive, and resilient digital world.