AI-augmented Business Process Management Systems: A Research Manifesto

Marlon Dumas, Fabiana Fournier, Lior Limonad, Andrea Marrella, Marco Montali, Jana Rebecca Rehse, Rafael Accorsi, Diego Calvanese, Giuseppe De Giacomo, Dirk Fahland, Avigdor Gal, Marcello La Rosa, Hagen Völzer, Ingo Weber (Corresponding author)

Research output: Contribution to journalArticleAcademicpeer-review

54 Citations (Scopus)
431 Downloads (Pure)

Abstract

AI-augmented Business Process Management Systems (ABPMSs) are an emerging class of process-aware information systems, empowered by trustworthy AI technology. An ABPMS enhances the execution of business processes with the aim of making these processes more adaptable, proactive, explainable, and context-sensitive. This manifesto presents a vision for ABPMSs and discusses research challenges that need to be surmounted to realize this vision. To this end, we define the concept of ABPMS, we outline the lifecycle of processes within an ABPMS, we discuss core characteristics of an ABPMS, and we derive a set of challenges to realize systems with these characteristics.

Original languageEnglish
Article number11
Number of pages19
JournalACM Transactions on Management Information Systems
Volume14
Issue number1
DOIs
Publication statusPublished - 31 Jan 2023

Bibliographical note

Funding Information:
Work supported by the European Research Council via Advanced Grants PIX (834141) and WhiteMech (834228).

Funding

Work supported by the European Research Council via Advanced Grants PIX (834141) and WhiteMech (834228).

FundersFunder number
H2020 European Research Council834141, 834228

    Keywords

    • augmented business process
    • business automation
    • Business process management
    • explainability
    • trustworthy AI

    Fingerprint

    Dive into the research topics of 'AI-augmented Business Process Management Systems: A Research Manifesto'. Together they form a unique fingerprint.

    Cite this