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SECTION I

Compliance Alignment

All agentic governance must trace back to binding obligations. The Compliance Alignment layer ensures every AI agent operates within the boundaries of contracts, regulations, internal policies, and ethical principles.

6 Control Objectives
Risk-Driven Approach
Measurable Metrics

Why Compliance Alignment Matters

As autonomous AI agents make decisions and take actions on behalf of your organization, they inherit legal, regulatory, and ethical obligations. Without explicit compliance mapping, agents may inadvertently:

  • Violate customer contract terms or SLAs
  • Breach data protection regulations (GDPR, CCPA, HIPAA)
  • Produce biased or unfair outcomes causing reputational harm
  • Fail to maintain audit trails required by regulators

Key Principle

"Compliance is not a constraint on innovation—it's the foundation that enables sustainable, trustworthy AI adoption at enterprise scale."

Each control objective below addresses a specific compliance risk with measurable outcomes that can be tracked and improved over time.

Control Objectives

CMP-01

Contractual Obligation Mapping

Ensure every AI agent's capabilities and actions are explicitly mapped to the contractual obligations that govern them. This includes customer agreements, vendor contracts, and intellectual property terms.

Primary Risk Addressed

Agent actions violating contract terms

Key Metric

% agents mapped to governing contracts

CMP-02

Regulatory Requirement Traceability

Establish clear traceability between agent capabilities and applicable regulatory requirements. This ensures that compliance obligations are systematically linked to the features and functions each agent performs.

Primary Risk Addressed

Non-compliance with applicable regulations

Key Metric

% capabilities traced to regulatory requirements

CMP-03

Regulatory Change Detection

Implement monitoring systems to detect changes in applicable regulations and assess their impact on existing agents. Proactive detection prevents compliance drift as regulatory landscapes evolve.

Primary Risk Addressed

Compliance drift from evolving regulations

Key Metric

Time from regulation change to impact assessment

CMP-04

Internal Policy Adherence

Ensure agents operate within the boundaries defined by internal corporate policies, including acceptable use policies, risk appetite statements, and data classification requirements.

Primary Risk Addressed

Violation of corporate policies

Key Metric

Policy compliance audit findings

CMP-05

Ethical Principle Embedding

Embed ethical principles into agent design and operation, including fairness, transparency, and bias mitigation. Every agent should undergo ethics review before production deployment.

Primary Risk Addressed

Reputational harm from biased or unfair agents

Key Metric

% agents with ethics review completed

CMP-06

Compliance Evidence Retention

Maintain comprehensive records and evidence of compliance activities to demonstrate adherence during audits. This includes decision logs, policy mappings, and review documentation.

Primary Risk Addressed

Inability to demonstrate compliance under audit

Key Metric

Audit readiness score

Quick Reference

ID Objective Primary Risk Addressed Key Metric
CMP-01 Contractual Obligation Mapping Agent actions violating contract terms % agents mapped to governing contracts
CMP-02 Regulatory Requirement Traceability Non-compliance with applicable regulations % capabilities traced to regulatory requirements
CMP-03 Regulatory Change Detection Compliance drift from evolving regulations Time from regulation change to impact assessment
CMP-04 Internal Policy Adherence Violation of corporate policies Policy compliance audit findings
CMP-05 Ethical Principle Embedding Reputational harm from biased or unfair agents % agents with ethics review completed
CMP-06 Compliance Evidence Retention Inability to demonstrate compliance under audit Audit readiness score

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