Probabilistic risk assessment (PRA) methods will inform the licensing and oversight of advanced reactor designs (AR). PRA results will inform the selection of licensing-basis events, the safety classification of components, and the evaluation of defense-in-depth adequacy within the framework of the licensing modernization project endorsed by U.S. NRC.Reliable component failure data is a critical input to quantify PRA. However, for non-LWR (NLWR) designs, there is a gap in the operational failure data required to robustly quantify risk. The ANSI/ASME/ANS RA-S-1.4-2021 standard, which is the consensus PRA standard for NLWR plants, outlines requirements for 18 technical elements covering all hazards, operating states, and radiological sources covering design, construction and operation. Despite this, the absence of comprehensive reliability data for diverse operational conditions, coolants, and design configurations exacerbates the data gap. In addition to the above-mentioned licensing activities, these failure rates are also essential to support design validation activities, operational reliability and availability assessments, and broader reliability integrity management applications. Such a wide use of PRA data was not previously encountered with the current fleet, as both the licensing and oversight processes were informed deterministically. This paper underscores the importance of acquiring robust operational data and highlights the urgent need to prioritize the collection of historical, current, and future AR operational data to address these challenges effectively.