Monitoring of reclamation or restoration activities (“restoration monitoring” for brevity) is a crucial step in adaptive management not only to judge effectiveness of a restoration action but also to build evidence for its overall efficacy and context in which it is appropriate. Restoration monitoring should be targeted to detect the desired effects (and anticipated side effects) of the action. However, there is great value in adopting consistent monitoring indicators and methods to facilitate the use of existing data, leverage data quality and management processes already in place, and gain the ability to view restoration activities in the context of larger landscape monitoring efforts. The Bureau of Land Management’s (BLM) Assessment, Inventory, and Monitoring (AIM) program provides a strategy for monitoring the status and trend of BLM rangelands at multiple scales, report on the effectiveness of monitoring actions, and provide information necessary for BLM to implement adaptive management. The AIM strategy emphasizes a set of core indicators and methods and statistically-based sampling design to provide consistency and rigor to BLM monitoring. AIM is a flexible tool that can be applied to situations like restoration monitoring (e.g., via use of supplemental indicators) while retaining compatibility with larger scale monitoring efforts. There are several ways in which the AIM strategy or existing AIM data can be applied to restoration monitoring including: augmenting existing restoration monitoring; using in before-after-control-impact (BACI) sampling designs; comparing data from restoration sites to either nearby similar AIM sites or to a collection of AIM sites from the same land type; or comparison of restoration monitoring data to reference conditions developed from a larger collection of AIM data. We will illustrate each of these approaches through examples of where BLM has used AIM data for restoration monitoring in northwestern Colorado, northern New Mexico, and eastern Alaska.