The transition from traditional maintenance paradigms toward data-driven, intelligent asset management is redefining the role of maintenance in industrial strategy. This chapter introduces the digital shift in maintenance, positioning it as both a technological evolution and an organizational transformation. Building upon the foundations laid in Digital Maintenance Management (2022), it examines the accelerating convergence of operational technology (OT) and information technology (IT), and how emerging capabilities such as AI-driven diagnostics, digital twins, and cloud-edge architectures are reshaping decision-making and performance optimization. The chapter identifies key enablers—connectivity, standards, semantic interoperability, and governance frameworks—that support the scalable deployment of digital maintenance solutions. It also outlines persistent challenges including fragmented data ecosystems, skills gaps, cybersecurity threats, and the difficulty of aligning condition data with long-term investment decisions, the critical link between real-time condition monitoring and strategic asset value management. This introductory chapter serves to frame the structure of the book, offering a roadmap through the technological, organizational, and regulatory forces currently shaping maintenance transformation. It advocates for a layered, standards-based, and maturity-aligned approach to digitalization, recognizing that successful transformation is as much about culture and capability as it is about tools. By mapping key trends and tensions, the chapter sets the stage for deeper thematic analysis in subsequent contributions.