Mapping C3P Control Objectives to ISO/IEC 42001 Requirements for AI Lifecycle Governance
TL;DR
The central finding is that the same four points generalize without modification to AI coding agents and to general agentic workflows, where a defined purpose, an auditable trail, verification, and safe delivery produce tamper-evident evidence at every stage.
Abstract
This article examines how the four control objectives of the Continuous Compliance Control Protocol align with the requirements of ISO/IEC 42001 for managing an artificial intelligence system across its lifecycle, and how they generalize to autonomous agents. Organizations adopt artificial intelligence in regulated settings faster than they build the mechanisms that continuously prove governance, and a management system standard states what must be governed, while leaving open how durable evidence is produced as systems run. A baseline mapping establishes that the four control points meet the requirements of the standard for a conventional, human-in-the-loop deployment. The central finding is that the same four points generalize without modification to AI coding agents and to general agentic workflows, where a defined purpose, an auditable trail, verification, and safe delivery produce tamper-evident evidence at every stage. That evidence assembles into a chain of custody for the agent that supplies exactly the documentation an ISO/IEC 42001 audit expects. The work serves compliance leaders, audit professionals, and engineering teams who govern autonomous artificial intelligence.