This paper presents a historical excursus from the initial introduction of the Declare Framework to its potential future applications within the context of AI-Augmented Business Process Management Systems (ABPMSs). On this path, we highlight how AI related techniques have intertwined with research on the declare language, and how the core ideas of the original declare Framework have become even more relevant with the conception of ABPMS. With the latter, we refer to the use of multiple interdependent models of different languages to express a business process – an idea now consolidated as the multi-model paradigm. Within this paradigm, we explore the use of Automated Planning for operational support in executing multi-faceted constraints that involve multiple models, timeline limitations, cost constraints, and resource optimization. We position this approach as a more expressive way of modeling the process frame of an ABPMS, with the goal of maximizing a KPI or finding a trade-off among several of them.