"Dynamic Constitutional Control of Agentic Enterprise Digital Twins via Meta-Governor Agents"

"Enterprise digital twins are evolving from passive monitoring replicas into agentic, decision-capable cyber-physical intelligence layers that can observe, reason, plan, and act across complex operational ecosystems. However, as autonomy increases, static governance policies become insufficient to manage risk, drift, compliance changes, and human trust requirements. This paper proposes a Dynamic Constitutional Control (DCC) framework for agentic enterprise digital twins, enabled through Meta-Governor Agents (MGAs) that continuously supervise, constrain, and adapt autonomy policies in closed-loop operation. The proposed framework introduces a constitutional control layer that transforms enterprise governance principles into machine-enforceable control laws, enabling real-time adaptation of escalation thresholds, action boundaries, rollback rules, and human-approval checkpoints. Unlike existing guardrail-based approaches, DCC embeds governance directly into the decision loop of the twin, allowing policy evolution under operational risk, compliance drift, and feedback from human supervisors. We present a multi-layer architecture, formal control model, evaluation dimensions, and enterprise deployment scenarios spanning reliability engineering, financial risk systems, and healthcare workflow automation. The framework establishes a new systems paradigm for self-regulating, trust-adaptive, and human-sovereign enterprise autonomy.Keywords: Agentic AI, Enterprise Digital Twins, Constitutional AI, Meta-Governor Agents, Human-in-the-Loop, Autonomous Governance, Reliability Engineering"