While Business Process Engineering (BPE) has traditionally achieved optimization through structural standardization, the "implementation gap" remains a significant barrier to organizational agility. Empirical evidence suggests that nearly 60–70% of Business Process Management (BPM) initiatives fail to meet their initial strategic objectives, not due to technical misalignment, but because of a failure to account for human-process interaction. This paper challenges the prevailing deterministic view of workflows as mechanical sequences by proposing a transition from static process mapping to dynamic process cognition. By embedding Behavioral Systems Thinking (BST) into BPE frameworks, we address the cognitive overhead inherent in complex models; research indicates that model comprehension drops by approximately 20–30% as the number of gateways and non-sequential paths increases, leading to "process bypass" behaviors. We synthesize cognitive load theory, mental simulation, and systemic boundary objects to argue that process models must function as cognitive scaffolds rather than just technical artifacts. This multi-perspective approach integrates behavioral diagnostics, targeting the hidden 80% of process exceptions driven by human heuristics, with systems engineering to enhance predictive accuracy post-deployment. The resulting "Process Cognition" framework provides a robust methodological link for designing adaptive process architectures that are technically valid, cognitively aligned, and resilient within complex adaptive systems (CAS).