AI-augmented Framework to Enable Process Awareness in Collaborative Teams

Process Management Systems (PMS) offer effective means to coordinate tasks for various teams involved in complex projects. However, in practice, participants execute their tasks using applications within their workspace and manually report their activities to a separate PMS. This approach is not only time-consuming for end-users but also poses reliability challenges for the PMS in verifying the accuracy of reported task completion. This paper proposes an AI-augmented framework to establish seamless integration between PMSs and end-user workspace, which can automatically manage process execution by intelligently monitoring the tasks of process participants. We examined the utilization of our framework via a prototype pMage in a software implementation process. The results showcase the capability in managing process progress in various scenarios. The service effortlessly integrates the working environment with the corresponding process while maintaining its low-code applicability and independence from specific PMS or end-user workspace. This framework is anticipated to encourage end-users to embrace PMS as an integral part of their daily work, thereby unlocking the benefits of a process-aware workspace.