May 8, 2024, 4:42 a.m. | Michael Wornow, Avanika Narayan, Krista Opsahl-Ong, Quinn McIntyre, Nigam H. Shah, Christopher Re

cs.LG updates on arXiv.org arxiv.org

arXiv:2405.03710v1 Announce Type: cross
Abstract: Automating enterprise workflows could unlock $4 trillion/year in productivity gains. Despite being of interest to the data management community for decades, the ultimate vision of end-to-end workflow automation has remained elusive. Current solutions rely on process mining and robotic process automation (RPA), in which a bot is hard-coded to follow a set of predefined rules for completing a workflow. Through case studies of a hospital and large B2B enterprise, we find that the adoption of …

arxiv cs.ai cs.lg cs.se enterprise foundation type

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