AdONE Seminar: Prof. Fabrizio Maria Maggi (Free University of Bolzen-Bolzano)

This talk will discuss the evolution of AI-augmented Business Process Management focusing on how artificial intelligence can enhance process automation, improvement, and adaptability to change. In this context, we investigate the use of automated planning as a core mechanism to support framed autonomy. We define the process environment as a frame of multifaceted constraints, including declarative rules, procedural models, resource availability, costs, and deadlines. Each constraint is associated with a violation cost, capturing the criticality of the constraint in real-world process execution. Given a running process instance (i.e., a prefix) that may violate this frame, automated planning is used to compute an optimal continuation that minimizes the overall violation cost. In this way, the system can recommend or enact process adaptations that are the most feasible ones based on the given costs. Complementary to this perspective, we are also studying Neuro-Symbolic Predictive Process Monitoring (PPM) as another key direction in AI-augmented BPM. In this setting, predictive models based on neural networks are enriched with symbolic knowledge, enabling them to handle exceptional or rare situations that are not sufficiently represented in historical data. While neural components provide strong predictive capabilities, symbolic knowledge supports reasoning beyond the data, improving robustness and adaptability to process change.