AI

Adaptive Workflow Intelligence: A Cognitive Architecture for Context-Driven Enterprise Automation

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Briefings

This paper introduces Adaptive Workflow Intelligence (AWI), a cognitive architecture for enterprise agents organized around a four-layer Perception-Cognition-Action-Reflection (PCAR) loop. AWI combines hybrid reasoning with reflective memory and feedback-driven adaptation to support decision-making under environmental drift and operational constraints. The study evaluates AWI in a simulated enterprise decision workflow characterized by delayed outcomes and a controlled regime shift, finding that guardrail-constrained adaptive approaches recover more rapidly than static automation while maintaining policy compliance.

Key points

• AWI is a cognitive architecture for enterprise agents organized around a four-layer Perception-Cognition-Action-Reflection (PCAR) loop.
• AWI treats reflection as a mechanism for continuous policy refinement and combines hybrid reasoning with reflective memory and feedback-driven adaptation.

Context and limitations

The evaluation was conducted in a simulated enterprise decision workflow with delayed outcomes and a controlled regime shift, limiting generalizability to real-world dynamic environments.

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