Towards an AI-Agent-Based Framework for Agile Business Process Management

Abstract

The traditional approaches in dynamic and collaborative environments that use Business Process Management (BPM) methodologies usually lack the ability to adapt to real-time changes in case of heavy human involvement in repetitive processes. The agility of social BPM is, however, still limited because of a lack of context-sensitive tool support. This paper proposes a mapping framework that leverages conversational AI agents on a social media platform to enhance BPM agility. AI-driven conversational agents are mapped to the respective phases of the BPM lifecycle to provide real-time guidance, recommendations, and context-sensitive feedback. The agents’ collaborative features enable inclusive co-construction, interactive task execution, and continuous monitoring of the processes. That allows dynamic adaptation of the processes in case of changes so that tasks remain aligned with the users’ needs and contextual demands. This framework is developed through an exploratory approach that integrates literature review, deductive design, and use case-based evaluation. This framework could bridge gaps in the current BPM practices by integrating BPM, AI, and social media, thereby offering a new model for agile and collaborative business process management.