Automation, control, and analysis of knowledge-intensive processes.

Process automation has been a widely used methodology for improving business processes since the late 90's. Typically, automation was applied to well-structured and highly routine business processes. Knowledge-intensive processes that exhibit ad-hoc workflows and involve mainly knowledge workers are now becoming more and more common in most industries. Traditionally, these processes were considered harder to model, analyze and thus automate due to their unstructured and flexible nature. Recent advances in the worlds of Artificial Intelligence and Machine Learning supported by ample data availability has led to developments in knowledge-intensive process modeling, analysis, and automation. Specifically, applications such as natural language processing and information retrieval allows researchers to identify workflows in unstructured data (e.g., emails) and map ad-hoc behavior to workflow patterns. In this workshop, we aim at sharing experiences and research results on recent advances in data-driven approaches to process automation with a special emphasis on ad-hoc business processes, i.e., work patterns with no predefined process models. The workshop will explore theories, algorithms, and engineering methods at the intersection of AI and process management to develop next generation intelligent business automation solutions. Speakers will be researchers and industry leaders from diverse backgrounds including but not limited to process automation in knowledge-intensive processes, business process management, data-driven activity and workflow recognition, and flexible process mining using constraint learning. The workshop will give the audience a broad exposure to the field, and create opportunities for collaborations among academic research groups and industry teams between various partners that wish to develop The workshop will run as a single-session online event and will be adjusted to the special circumstances of the new normal under COVID-19 restrictions.