Power electronics facilitated the growth of a wide range of industries in today’s world. Its presence can be seen in renewable energy systems, transportation electrification, smart grids, industrial drives, and consumer electronics to name a few. At the heart of the power electronics industry is the semiconductor, as power electronics rely on the semiconductor industry. With the advancements of wide bandgap semiconductor devices, many new power electronics solutions are becoming viable to realize and implement. Maintaining, prognostic, and protecting the aforementioned semiconductor devices require various compatible sensing solutions to enable intelligence and reliability. In this context, a novel sensing solution is proposed, designed, and implemented for modern power management systems. This sensing solution generates the current difference data of adjacent paralleled wide bandgap devices used within power modules of converters/inverters. This new dataset can be exploited with different topologies and machine-learning algorithms for prognostics and protection purposes. The concept is proven in this work through electromagnetic field simulation and analysis, as well as several experimental-level prototypes. Besides maintenance, control and over-current detection are essential parts of all power electronic systems. Many high-efficiency and fast-response control and detection technologies are reliant on semiconductor switch current measurement. The accuracy and speed of such employed current sensors would dictate the performance of the overall system, consequently, for modern power electronics, compatible switch current sensing solutions need to be researched and developed. On this matter, a novel unidirectional Rogowski switch current sensor is proposed, developed, and tested in the scope of this work. The prototyped switch current sensor is capable of measuring the fast switching current of wide bandgap semiconductor devices, including a novel compensation technique for DC measurement errors. Both proposed sensing solutions are well promising to help create reliable and intelligent power management systems.