The importance of monitoring for adaptive management of rangelands has been well established. However, the actual use of monitoring data in rangeland management decisions has been modest despite extensive efforts to develop and implement monitoring programs from local to national scales. More effective use of monitoring data is critical to inform adaptive management, to empirically justify management decisions, and to ensure a return on resources invested in monitoring programs like the Bureau of Land Management’s (BLM) Assessment, Inventory, and Monitoring (AIM) program. Several challenges limit the use of monitoring data in management decision making. First, there is often a disconnect between aspects of monitoring (e.g., indicators, sample design, timing) and information needs of managers for making decisions. This can arise from a lack of specific monitoring objectives tied to management decisions or from monitoring indicators being analyzed and presented in forms that do not mesh with land management workflows. Second, in many cases little information exists on how to interpret monitoring results with respect to land potential (e.g., is the amount of bare ground more than what is expected for this type of rangeland?). Third, given limited resources, monitoring data often produce estimates with large confidence intervals, which causes challenges for interpreting whether a change has occurred or a land health standard has been met. Fourth, there is a tension between flexibility to design monitoring around management needs for specific, immediate objectives and maintaining standard monitoring approaches to build long-term datasets. This has the effect of reinforcing short-term monitoring at the expense of investing in standardized efforts that could address multiple objectives over the long term. We describe these challenges in the context of the BLM AIM projects discussed during the symposium. We explore potential opportunities for addressing these challenges and how the AIM program can be leveraged for success.