AI is revolutionizing the way business processes are executed and managed in every domain. The IDC report “Worldwide Artificial Intelligence and Automation 2023 Predictions” forecasts, somewhat optimistically, that by 2026, 75% of large enterprises will rely on AI-driven processes to enhance asset efficiency, streamline supply chains, and improve product quality across diverse and distributed environments. AI can improve business process management in several ways, including automated process improvement, redundant and tedious task automation, and predictive monitoring and prescriptive execution. AI may also assist business stakeholders in design-time change decisions, automating repetitive and “mechanical” tasks, and triggering predefined actions to respond to anticipated changes.

Advances in AI make it possible to push the boundaries of automation into the realm of Autonomous Business Processes (ABPs). In ABPs, AI-based systems not only recommend predefined interventions, as in prescriptive process execution, but they also proactively trigger interventions to respond to unforeseen changes within user-defined constraints. ABP is a frontier research challenge in the field of BPM. The initial vision towards ABP was recently introduced in the “AI-augmented Business Process Management Systems: A Research Manifesto.” This manifesto coined the concept of AI-Augmented Business Process Management Systems (ABPMSs), their lifecycle, core characteristics, and the research challenges they present. ABPMSs are an emerging class of process-aware information systems empowered by trustworthy AI technologies. An ABPMS enhances the execution of business processes with the aim of making these processes more adaptable, proactive, explainable, and context sensitive. The most advanced form of ABPMSs is manifested by ABP systems.

This Dagstuhl Seminar aims to bring together academic and industrial researchers from the AI and BPM communities to foster joint efforts and collaboration to advance the vision of ABP and address the challenges outlined in the manifesto including crucial limitations and risks. The seminar will cover topics at the intersection of AI and business process management systems, potentially contributing to the advancement of ABPMSs, including declarative process specification and reasoning with a focus on framed autonomy; planning and program synthesis; explainable and trustworthy AI; conversational systems and natural language processing; causal discovery and neuro-symbolic reasoning; self-healing and auto-corrective techniques; large foundation models; and legal, safety, and ethical aspects of autonomous enterprises.

The main goal of the seminar is to compile a research agenda toward the realization of ABP systems. A second goal is to capitalize on the collective expertise of the participants by establishing a network of excellence in ABP. This network of excellence could bring together a broad and inclusive range of AI and BPM researchers and practitioners, providing a platform for launching future workshops, research contests, collaborative research projects, industrial transformation initiatives, and technology transfer activities in the direction of ABPs. As a direct result of this seminar, we aim to release a white paper detailing the concrete research challenges, promoting the continuation of research work on ABPs, and disseminating the seminar's results to realize the different challenges that unfold from its vision.