Highly pathogenic avian influenza virus of the H5N1 subtype has been infecting U.S dairy cattle and spreading among dairy farms since March 2024. H5N1 surveillance systems for dairy farms are needed, but information on whether environmental sampling can inform these systems is lacking. To guide a surveillance framework, we determined the environmental locations on H5N1-affected dairies (n = 25) in four states (California, Colorado, Michigan, and Ohio) that harbored influenza A virus (IAV), and explored sample characteristics that may influence viral detection. A total of 623 samples from environments and sale barns were characterized for IAV and classified into six categories based on location. A total of 94 samples (15.1%) had IAV detected, the majority in the following categories: milking equipment/personal protective equipment, parlor surfaces, and wastewater/lagoons/manure. These results suggest that dairy environments most likely to harbor IAV are those with exposure to milk, although the viral load in environmental samples was typically lower than that of bulk tank milk tested on a subset of farms. Mixed effect modeling was used to explore the relationship between IAV detection, Ct value, and days into an outbreak that samples were collected or the category where samples were collected. Days into an outbreak that samples were collected was associated with IAV detection while category of collection was associated with the measured Ct value. These results may guide H5N1 surveillance efforts on dairies, and can be strengthened by studies that collect samples from farm environmental locations prior to, during, and after H5N1 outbreak periods.