AI-augmented Business Process Management Systems (ABPMSs) are an emerging class of process-aware information systems empowered by AI technology for autonomously unfolding and adapting the execution flow of business processes (BPs). A central characteristic of an ABPMS is the ability to be conversationally actionable, i.e., to proactively interact with human users about BP-related actions, goals, and intentions. While today's trend is to support BP automation using reactive conversational agents, an ABPMS is required to create dynamic conversations that not only respond to user queries but even initiate conversations with users to inform them of the BP progression and make recommendations to improve BP performance. In this paper, we explore the extent to which state-of-the-art conversational systems (CSs) can be used to develop such proactive conversation features, and we discuss the research challenges and opportunities within this area.

Conversational Systems for AI-Augmented Business Process Management / Casciani, Angelo; Bernardi, Mario L.; Cimitile, Marta; Marrella, Andrea. - 513:(2024), pp. 183-200. (Intervento presentato al convegno Research Challenges in Information Science tenutosi a Guimaraes; Portugal) [10.1007/978-3-031-59465-6_12].

Conversational Systems for AI-Augmented Business Process Management

Angelo Casciani
;
Andrea Marrella
2024

Abstract

AI-augmented Business Process Management Systems (ABPMSs) are an emerging class of process-aware information systems empowered by AI technology for autonomously unfolding and adapting the execution flow of business processes (BPs). A central characteristic of an ABPMS is the ability to be conversationally actionable, i.e., to proactively interact with human users about BP-related actions, goals, and intentions. While today's trend is to support BP automation using reactive conversational agents, an ABPMS is required to create dynamic conversations that not only respond to user queries but even initiate conversations with users to inform them of the BP progression and make recommendations to improve BP performance. In this paper, we explore the extent to which state-of-the-art conversational systems (CSs) can be used to develop such proactive conversation features, and we discuss the research challenges and opportunities within this area.
2024
Research Challenges in Information Science
AI-augmented Business Process Management; Conversational Systems; Large Language Models; Process Mining
04 Pubblicazione in atti di convegno::04b Atto di convegno in volume
Conversational Systems for AI-Augmented Business Process Management / Casciani, Angelo; Bernardi, Mario L.; Cimitile, Marta; Marrella, Andrea. - 513:(2024), pp. 183-200. (Intervento presentato al convegno Research Challenges in Information Science tenutosi a Guimaraes; Portugal) [10.1007/978-3-031-59465-6_12].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1718089
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