Program design
Connect policies, roles, training, reporting channels, and review into an operating model people can use.
ARH Ethics & Governance · Pillar 02
A compliance program is not a binder of rules. It is a proportionate way to connect obligations, people, controls, information, escalation, and continuous improvement to the work an organization actually does.
A practical orientation
This pillar organizes the practical questions beneath program design: what obligations and risks are material, who owns the control, what evidence supports oversight, and how does the organization learn when conditions change? It offers general educational context rather than a determination of any entity’s legal or regulatory requirements.
“The discipline is not knowing every answer in advance. It is creating a responsible way to recognize the question, involve the right people, and follow through.”
The compliance record
Use these as an orientation to the questions, tensions, and decision practices that deserve clear ownership and continuing review.
Connect policies, roles, training, reporting channels, and review into an operating model people can use.
Make risk information decision-useful by tying it to products, people, transactions, third parties, and change.
Clarify the control objective, owner, evidence, exception path, testing, and remediation loop.
Related advisory work
These routes connect the pillar to the existing advisory and educational materials within the ARH public archive.
A decision-led framework for risk, ownership, reporting, and review.
Open record Advisory recordAccountable oversight for AI-enabled decisions, controls, and reliance.
Open record Advisory recordBoard, management, culture, and accountability in a shared decision architecture.
Open recordCross-cutting pathway
AI-enabled decisions can introduce new questions of authority, risk, transparency, oversight, and documentation. The AI Governance record connects these questions across ethics, compliance, and governance without treating technology as a separate responsibility.
Explore AI Governance and AI EthicsResource library