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With the increased deployment of AI-based technologies—recently and most notably large language models—framing the autonomy of goal-oriented agents that enact business processes can be expected to be a key challenge. In this paper, we argue that addressing this challenge requires new formal foundations for process specifications. Traditional business process specifications focus on the how of business operations and treat neither goals nor norm-based constraints as first-class abstractions. Although goals play a central role in informal notions of business processes, formal definitions tend to treat them as implicit, embedded within procedural specifications that may only partially, and not explicitly, reflect normative boundaries. However, to maximize autonomy within a given normative frame, which expands upon the traditional idea of process models as operational frames, agents require formally specified goals, from which they can then synthesize their plans and actions, considering the normative frame as a set of deontic constraints. In this paper, we articulate this vision, highlight practical challenges, and propose action items for supporting its implementation.