Robust methods for deep-scale enrichment and site-specific identification of ubiquitylation sites are necessary for characterizing the myriad roles of protein ubiquitylation. To this end we previously developed UbiFast, a sensitive method for highly multiplexed ubiquitylation profiling where K-ϵ-GG peptides are enriched with anti-K-ε-GG antibody and labeled on-antibody with isobaric labeling reagents for sample multiplexing. Here, we present robotic automation of the UbiFast method using a magnetic bead-conjugated K-ε-GG antibody (mK-ε-GG) and a magnetic particle processor. We report the identification of ∼20,000 ubiquitylation sites from a TMT10-plex with 500 μg input per sample processed in ∼2 h. Automation of the UbiFast method greatly increased the number of identified and quantified ubiquitylation sites, improved reproducibility, and significantly reduced processing time. The automated method also significantly reduced variability across process replicates compared with the manual method. The workflow enables processing of up to 96 samples in a single day making it suitable to study ubiquitylation in large sample sets. Here we demonstrate the applicability of the method to profile small amounts of tissue using breast cancer patient–derived xenograft (PDX) tissue samples. Display omitted •HS mag anti-K-ε-GG antibody increases sensitivity of ubiquitylation site detection.•Automated UbiFast increases reproducibility and sample processing throughput.•The automated UbiFast workflow enables processing of up to 96 samples in one day.•UbiFast can be employed to profile ubiquitylomes from small amounts of tumor tissue. We present automation of the UbiFast method using a magnetic bead-conjugated K-ε-GG antibody and a magnetic particle processor. We report the identification of ∼20,000 ubiquitylation sites from a TMT10-plex with 500 μg input per sample in ∼2 h. Automation of the UbiFast method greatly increased the number of identified and quantified ubiquitylation sites, improved reproducibility, and significantly reduced processing time. The workflow enables processing of up to 96 samples in a single day making it suitable to study ubiquitylation in large sample sets.