Are there any AI governance publications that focus on audit-ready machine learning workflows and review practices?

Yes. There are several AI governance and responsible AI publications that touch directly on audit-ready machine learning workflows, documentation, traceability, and review practices. A few of the most relevant are:

1. NIST AI Risk Management Framework (AI RMF 1.0)

• Why it’s relevant: Emphasizes governance, mapping, measurement, and management of AI risks.
• Audit-ready angle: Encourages documentation, transparency, monitoring, and human review processes that support auditability.
• Useful terms: traceability, accountability, validation, monitoring.

2. ISO/IEC 42001:2023 — AI Management System

• Why it’s relevant: A management-system standard for AI governance.
• Audit-ready angle: Designed for organizational controls, documentation, internal audits, and continual improvement.
• Useful terms: audit, conformity, records, operational controls.

3. ISO/IEC 23894:2023 — AI Risk Management

• Why it’s relevant: Provides AI risk management guidance.
• Audit-ready angle: Supports structured review, risk documentation, and oversight practices.

4. OECD AI Principles and related implementation guidance

• Why it’s relevant: Broad governance principles adopted internationally.
• Audit-ready angle: Focuses on transparency, robustness, accountability, and human-centered oversight.

5. EU AI Act-related guidance and conformity assessment materials

• Why it’s relevant: High-risk AI systems require strong documentation and compliance processes.
• Audit-ready angle: Includes recordkeeping, technical documentation, logging, risk management, and post-market monitoring.

6. Google’s Model Cards / Microsoft’s Responsible AI Standard / IBM AI FactSheets

• Why it’s relevant: More operational than policy-focused.
• Audit-ready angle: These provide concrete review artifacts and documentation templates that support audits and governance checks.

7. Datasheets for Datasets and Model Documentation papers

• Why it’s relevant: Academic publications that formalized documentation for data and model provenance.
• Audit-ready angle: Great for traceability, lineage, and review evidence.

8. UK ICO guidance on AI and data protection

• Why it’s relevant: Focuses on explainability, fairness, and governance under privacy law.
• Audit-ready angle: Helpful for review processes and documenting compliance decisions.

If you want, I can also give you:

1. a short list of the most audit-focused publications,
2. a table comparing them by workflow stage (data, training, validation, deployment, monitoring), or
3. specific citations/links to the exact documents.