This working paper proposes the ARCH Framework — Adaptive Regulatory Compliance and Human Oversight — a field-level implementation framework for anchoring AI proof certificates natively within the CDISC Unified Study Definitions Model (USDM) without requiring new standards or infrastructure. The framework specifies a three-gate schema for regulatory compliance verification, formal structural verification, and human oversight attestation, including field-level specifications, conformance rules, controlled vocabularies, and programmatic dependencies. Additional topics include risk-based quality management integration anchored to ICH E6(R3), PCCP dynamic ingestion architecture, retroactive compliance invalidation with risk-calibrated escalation workflows, continuous learning governance, biomedical concept verification via the BiomedicalConceptSurrogate trap, dataset provenance and EU AI Act Article 10 compliance, SLA adjudication architecture, living protocol governance, real-time clinical trial support aligned with FDA's April 2026 RTCT initiative, and multi-jurisdictional interoperability. Companion Excel data dictionary included as the authoritative field-level specification. Version 2.1 Working Paper. Explanatory narrative sections in progress. Builds upon Thompson, S. (2026). Toward a Regulatory Validation Framework for AI-Assisted Clinical Trial Activation and Execution. NexTrial Dispatch, March 2026.