Agentic AI Auditability & Assurance White Paper 2026
A Lifecycle Evidence Guide for Audit, Assurance, and Enterprise AI Governance
A lifecycle evidence guide for auditability, assurance boundaries, and enterprise AI governance.
A public research edition defining agentic AI auditability, lifecycle evidence, audit evidence chains, AARM, MRO-to-audit-evidence mapping, and enterprise AI governance boundaries.
Research object and scope.
The Agentic AI Auditability & Assurance White Paper 2026 turns lifecycle responsibility into audit evidence: reconstructable authority, roles, tool actions, accepted outcomes, exceptions, remediation, and privacy-preserving disclosure.
Who this artifact is for.
First public research edition establishing the auditability and assurance companion to GAIC.
What a reader can decide from this paper.
What makes agent work auditable beyond raw logs and traces?
A visible output is not enough to reconstruct who acted, under what authority, against which intent, and why the outcome was accepted.
- Defines the agentic audit object.
- Separates logs from audit evidence chains.
- Provides an assurance-boundary vocabulary for lifecycle review.
Use this paper to scope an evidence review and identify which lifecycle records are still missing.
It does not provide an audit opinion, assurance conclusion, certification, regulator approval, or legal-compliance proof.
Audit, assurance, security, and enterprise AI governance readers.
Why this paper matters.
It distinguishes raw logs from audit evidence chains and keeps auditability as a bounded evidence discipline rather than an audit opinion, certification, or assurance conclusion.
Read, download, and verify.
HTML and PDF are available. Manifest and checksum records are provided for integrity verification. No public DOCX is authorized.
Citation and identity.
Jearon Wong. Agentic AI Auditability & Assurance White Paper 2026: A Lifecycle Evidence Guide for Audit, Assurance, and Enterprise AI Governance. Technical Report AIAAWP-2026-v0.1, May 2026.
- Title
- Agentic AI Auditability & Assurance White Paper 2026
- Subtitle
- A Lifecycle Evidence Guide for Audit, Assurance, and Enterprise AI Governance
- Author
- Jearon Wong
- Version
- v0.1 Public Research Edition
- Document ID
- AIAAWP-2026-v0.1
- Publication month
- May 2026
- Canonical URL
- https://www.jearonwong.com/research/agentic-ai-auditability-assurance-white-paper-2026/
Public Research Edition. HTML/PDF artifacts are publicly available as a public research edition; not legal advice, not an audit standard, not certification, not an assurance opinion, and not regulator or audit-body endorsement.
- Not an audit standard.
- Not certification.
- Not legal advice or legal compliance proof.
- Not an assurance opinion.
- Not regulator approval.
- Not Big Four or audit-body endorsement.
- Not procurement recommendation or vendor ranking.
- No public DOCX is authorized.
Manifest and checksum record.
The public artifacts are available through the public route with manifest and checksum integrity records while preserving the controlled source-truth boundary.
163a5aa4c307222adda7eaef49c3cb2fa06dc9c8a856dd140ed285dff089f9df85cccf7c177d7f449d33d4d507cc4885828fe334c4715e338282197150423ac71b7a66da31e050c145c923fe20bdf33fc295c052f361007904722c7a179900d1ff495b01cec9db124cb7b2c0032db50d4d05a3db5c2ebb95f6d78a30b378500eWhat this paper does not claim.
Boundary language is part of the publication system. It keeps the artifact useful without turning research framing into external authority, advice, endorsement, certification, or standards-body approval.
- Not an audit standard.
- Not certification.
- Not legal advice or legal compliance proof.
- Not an assurance opinion.
- Not regulator approval.
- Not Big Four or audit-body endorsement.
- Not procurement recommendation or vendor ranking.
- No public DOCX is authorized.
Same publication system, adjacent research.
These white papers share the same public artifact pattern: title and abstract, status panel, HTML/PDF access, citation identity, manifest/checksum integrity, and explicit boundary notes.