SAAF AI Governance Template

Time to Complete: 30–45 minutes per AI capability

Purpose: Confirm that the AI use case or system is ready for enterprise-wide deployment. Covers governance, ethical considerations, privacy, fairness, transparency, compliance, monitoring, and education components.

Why Use This? Even successful pilots can fail in production if governance, ethical standards, compliance, or operational readiness aren’t in place. This governance template helps prevent surprises by ensuring comprehensive readiness across ethical, regulatory, and organizational dimensions.

1. Governance Overview

Clearly define your organization's approach to responsible AI:

• Purpose and scope

• Core principles (e.g., fairness, transparency, privacy)

2. Roles and Responsibilities

Establish clear accountability:

• AI Governance Lead (owner)

• Cross-functional AI Governance Committee (oversight)

• Executive Sponsor (strategic support)

3. Ethical AI Standards

Outline ethical guidelines to ensure responsible AI use:

• Acceptable vs. unacceptable AI applications

• Requirements for human oversight

• Processes for ethical review and escalation

4. Data Privacy and Protection

Embed privacy into AI practices:

• Compliance with privacy laws (GDPR, CCPA, etc.)

• Data minimization and anonymization practices

• Handling user consent and automated decisions

5. Bias and Fairness Management

Maintain fairness and prevent discrimination:

• Procedures for bias detection (use tools like IBM AI Fairness 360)

• Standards for representative data selection

• Guidelines for addressing and mitigating identified biases

6. Transparency and Auditability

Ensure AI systems can be explained and verified:

• Requirements for model documentation (e.g., Model Cards)

• Procedures for regular auditing and model reviews

• Mechanisms for providing explainability to stakeholders

7. Regional Compliance Checklist

Stay compliant across global operations:

• U.S.: Follow NIST AI RMF, sectoral regulations

• EU: Adhere to AI Act requirements based on risk levels

• APAC: Implement country-specific voluntary frameworks or mandatory guidelines (e.g., Singapore's Model AI Framework, China's algorithm registry)

8. Monitoring and Continuous Improvement

Regularly review AI governance effectiveness:

• Establish review cycles (quarterly, bi-annually)

• Process for capturing feedback and incidents

• Continuous refinement based on lessons learned

9. Education and Enablement

Promote AI literacy and governance understanding:

• Training requirements for relevant staff

• Resources for ongoing learning (e.g., workshops, toolkit updates)

• Communication channels for governance updates and clarifications

Implementation Notes:

• Customize each section based on your organizational context and scale.

• Regularly update to reflect evolving standards and regulations.

Adopting this governance template will provide clarity, accountability, and alignment across your organization, facilitating responsible AI adoption at scale.