management end-to-end mission requires appropriate internal governance¿depending on the business framework¿and the development of decision aid models (for asset replacement and maintenance), supported on probabilistic risk and reliability indexes. This book advocates systematically digitalizing the power and gas assets, addressing both data governance and infrastructure, alongside real-time equipment condition monitoring. It also provides a meaningful methodology for designing data-centric asset management and predictive operation and maintenance, using artificial intelligence and engineering-based approaches. As such, it provides valuable strategy, methods and models¿illustrated by case studies and proofs of concept¿for a wide range of stakeholders, including utilities and industry professionals, regulators, policy-makers, researchers and students.