Partial discharge (PD) detection has been always a fundamental tool, potentially, for the design, quality control, commissioning, and reliability monitoring for the of insulation systems. The word “potentially” stems from the objective consideration of the intrinsic limitations suffered by the existing partial discharge, PD, measurement technologies, especially the need of experts to interpret results and the lack of clear correlation between PD-related quantities, and the condition-based maintenance approach. On the whole, a thorough revision of insulation systems design procedures and of the tools to evaluate aging and failure risk is needed, especially in components of electrical assets which are critical in terms of reliability, resilience, and safety. This paper focuses on critical asset components, such as ships, aircrafts, aerospace, and any type of vehicles, where the coming electrification is significantly increasing nominal voltage, power density and efficiency, and where power electronics is the operative core. A new design approach, PD-free and reliability redundant, is briefly discussed, highlighting the importance to develop an innovative PD detection and analytics approach where measurements and interpretation are fully automatic and unsupervised, and experts are replaced by artificial intelligence. The aim is to remove the adverb “potentially” applied to the usefulness of PD detection and monitoring. The application of this innovative PD technology to measurements on dedicated test objects, able to incept either internal or surface discharges, or both, show how the capability to identify automatically the source typology of PD can help both in insulation system design and in devising health-condition monitoring systems for the asset components.