Bats are difficult to study due to their nocturnal, cryptic, and highly vagile nature. Ongoing advances in acoustic recording hardware and call classification software have made species detection and activity monitoring more feasible. Our objectives were to determine the effort necessary to monitor bat assemblages using an occupancy framework and acoustic data and to provide guidelines for researchers interested in developing similar monitoring programs. We collected data at 2 study areas in South Texas from June through September in 2015, 2016, and 2017. We used Pettersson D500X Mk II real-time full-spectrum detectors and classified sound files using SonoBat bat call analysis software. We attempted to collect data during 2 visits to individual sites, with up to 5 consecutive nights per visit each year. We estimated occupancy rates for each species in each study area using occupancy models in Program MARK and included terms to define trends in detection probability through the season. Over the 3 years of our study, we sampled 106 sites with 803 sampling nights and classified a total of 2880 sound files to 7 species. Data sets for 6 of the species supported models indicating that detection probability varied throughout our sampling period. Our results generally indicate that sample sizes between 10 and 20 sites would be required to detect declines in occupancy of 50% over 25 years using 10 nights per site with a starting occupancy rate of 0.70. Detecting declines of 30% in 10 years may require >75 sampling sites. Finally, our analysis shows that recognizing seasonal variation in detection probability, and then timing surveys accordingly, can greatly reduce sample size requirements.