The extraordinary development of AI techniques is paving the way toward a new generation of information systems able to "augment" process management, making them more autonomous, adaptive, intelligent, and self-optimizing. Such systems are referred to as AI-augmented BPM systems (ABPMS). These are AI-empowered, trustworthy, and process-aware systems that continuously reason and act on data within a set of constraints, with the aim of adapting and improving one or more processes according to various indicators. ABPMSs are the backbone necessary to realize the future enterprise's vision, enabling organizations to gradually shift their process management, advancing along the six levels of autonomous process execution management.

Achieving a synergetic combination of AI and process mining (PM) poses foundational, conceptual, and technical challenges related to the integration of symbolic and sub-symbolic AI techniques, and how to infuse them within PM. At the same time, delegating autonomy brings pressing requirements on the trustworthiness of such systems and on their ability to interact with human experts and explain their own behavior.

The third workshop on Process Management in the AI era (PMAI) aims at bringing together researchers from different research disciplines and a strong interest in promoting the synergy between AI and PM to address the above frontier challenges. It is co-located with the 27th European Conference on Artificial Intelligence, which will be held in Santiago de Compostela, Spain, in October 2024.

The event is planned as a one-day workshop, with selected peer-review papers and an invited talk session. Topics of interest for submission include, but are not limited to:

• multi-perspective process models (including data, time, and resources);
• declarative processes;
• explainable and trustworthy AI for process management and process mining;
• conversational systems, natural language processing, and human-machine interaction for process management;
• KR for process management: reasoning about actions and processes, planning, and synthesis;
• AI techniques for process discovery, conformance checking, prescriptive and predictive monitoring;
• AI techniques for clustering and classification of process execution traces;
• machine learning for event recognition on semi-structured and unstructured data;
• association rule mining, specification mining, and decision mining from process execution traces;
• declarative-based multi-perspective representation of process traces;
• novel metrics for the measurement of process conformance;
• uncertainty in AI for process management;
• multiagent systems, strategic reasoning, game theory, and mechanism design for multi-party processes;
• multi-objective optimization, decision-making, and continuous improvement;
• value alignment in process management.

Submissions must be written in English, prepared using the new CEUR-ART 1-column style, formatted in PDF, and submitted through Chairingtool https://chairingtool.com/conferences/PMAI24/MainTrack. PMAI 2024 invites submissions of research, industry, and application contributions. There are two submission formats:

Regular papers

(11-12 pages including an appropriate number of references): must contain enough substance that they can be cited in other publications and may not have appeared before.

Extended Abstracts

(2-4 pages including an appropriate number of references): results and ideas of interest to the PMAI audience, including position papers, system and application descriptions and presentations of preliminary results, an overview of papers accepted at another conference or which you submitted or plan to submit to another conference. In the latter case, extended abstracts must clearly state the venue where the paper has been accepted or submitted alongside its status.

All accepted papers will be published in the volume series of CEUR-WS. Depending on the number and quality of submissions, we will consider inviting authors of a selection of papers to submit extended versions for potential publication in a special issue of a journal.

For more information, visit https://pmai2024.demacs.unical.it/