The North American Breeding Bird Survey (BBS) is one of the longest annual avian surveys and has the greatest spatiotemporally extensive coverage in the Western Hemisphere. Although this important survey provides trend estimates for more than 400 species, it has limited coverage in the boreal forest and biases in representation and detectability that complicate inference. Thus, there is a need to evaluate the potential of new technologies and analytical approaches to increase coverage and improve monitoring efficiency. We documented variation in counts between BBS surveys (hereafter "human BBS") and different on-road and forest-edge surveys using autonomous recording units (ARUs) from 3 routes in the Northwest Territories, Canada. Specifically, we quantified percent differences (i.e., bias in counts) in species richness, abundance indices of birds, and species-specific variation in counts between human BBS and ARU-based surveys conducted on-road and at the forest edge at different dates and times of day. We also generated on-road effective detection radius (EDR) estimates for 15 species and tested for species-specific differences in EDR to explain bias in counts between on-road and forest-edge ARU surveys. Overall, species richness and abundance indices in human BBS surveys were higher than forest-edge ARU surveys conducted simultaneously and when similar forest-edge ARU surveys were conducted at sunset and a week earlier in June. However, there was no difference when comparing values from human BBS with on-road ARU BBS and forest-edge ARU surveys conducted at sunrise. Extracting the maximum count per species from 4 types of 3-minute forest-edge surveys increased counts by 62% and 64% for species richness and abundance indices, respectively, relative to human BBS, but the importance of this bias differed considerably among the 10 most common species in the study area. Our results suggest that false-negative bias in species detection could be corrected with appropriate methods, and ARUs deployed at the forest edge near BBS stops could be used to increase data quality of on-road surveys. When combined with appropriate correction factors to adjust for surveys done at the forest edge, ARUs could also be used to increase the geographic coverage of boreal surveys by allowing inexperienced volunteers to collect BBS data along winter or secondary roads in remote locations.