Innovative methods for evaluating viral risk and spread, independent of test-seeking behavior, are needed to improve routine public health surveillance, outbreak response, and pandemic preparedness. Throughout the COVID-19 pandemic, environmental surveillance strategies, including wastewater and air sampling, have been utilized alongside widespread individual-based SARS-CoV-2 testing programs to provide population-wide data. To date, environmental surveillance strategies have mainly relied on pathogen-specific detection methods to monitor viruses through space and time. However, this provides a limited picture of the virome present in a sample, leaving us blind to most circulating viruses. In this study, we explore whether virus-agnostic deep sequencing can improve the utility of air sampling to detect human viruses captured in air samples. We show that sequence-independent single-primer amplification sequencing of nucleic acids from air samples can detect common and unexpected human respiratory and enteric viruses, including influenza virus type A and C, respiratory syncytial virus, human coronaviruses, rhinovirus, SARS-CoV-2, rotavirus, mamastrovirus, and astrovirus.