AI OSI is an independent governance architecture for making AI decisions traceable, auditable, and defensible.
It defines the evidence layer required to reconstruct and defend high-risk and regulated AI decisions when they are examined later — often outside their original technical or organizational context.
Architecture, not policy. Evidence, not aspiration.
The Accountability Gap
The Governance Problem AI Has Created
Artificial intelligence now operates as institutional infrastructure.
It makes decisions, evolves over time, aggregates sensitive data, and influences material outcomes across healthcare, finance, public administration, and security.
Yet most organizations cannot answer basic questions:
What inputs were used?
How was the decision reached?
Was the reasoning legitimate at the time it was made?
Existing tools — model cards, ethics reviews, risk rubrics — do not create a defensible evidentiary chain.
They document intent, not accountability.
The Architecture
What AI OSI Is
AI OSI (Artificial Intelligence Open Standard Interconnection) is a layered governance architecture for artificial-intelligence systems.
It separates mandate, data, models, instruction, reasoning, deployment, and disclosure into explicit layers of accountability — each with defined obligations and evidence outputs.
This structure allows institutions to:
Identify where a failure occurred
Demonstrate oversight to regulators and auditors
Contain risk before it propagates
Produce governance evidence as a byproduct of normal operation
AI OSI is not related to the ISO OSI networking model. It adapts the principle of layered systems to governance.
Why Governance Breaks Down
Why AI Governance Fails Today
Most AI governance efforts focus on principles, policies, and intentions.
What they lack is infrastructure.
Documentation is fragmented. Reasoning is ephemeral. Accountability depends on post-hoc narratives assembled under pressure — often after systems have changed, staff have moved on, or vendors have rotated.
As a result, organizations are forced to explain AI decisions using incomplete records, informal judgments, or reconstructed logic that cannot withstand serious scrutiny.
AI governance fails not because standards are missing, but because evidence is.
The Governing Principle
Evidence, Not Policy
AI OSI treats evidence as a first-class system output.
Every significant AI decision is expected to generate structured artifacts that record:
Inputs and data lineage
Assumptions and constraints
Reasoning pathways and alternatives
Timestamps and contextual validity
These artifacts are designed to survive audits, disputes, and regulatory review — even when examined long after the decision was made.
This approach creates decision insurance: protection against negligent oversight, opaque failure, and unverifiable AI behavior.
The Governance Stack
How AI OSI Works: The Stack
The AI OSI Stack defines a multi-layer governance backbone for AI systems.
Each layer specifies:
Its scope of authority
Mandatory controls
Evidence that must be produced
Layers are designed to be implementation-neutral and compatible with existing AI toolchains, cloud environments, and model providers.
Governance is embedded upstream of execution systems, ensuring accountability survives system upgrades, vendor churn, staff turnover, and shifting legal regimes.
Intended Stewardship Roles
Who This Is For
AI OSI is intended for individuals and institutions that carry responsibility for AI outcomes, including:
Board directors and audit committees
General counsel and legal oversight teams
CISOs and cyber-risk leaders
Regulators, auditors, and governance bodies
Public-sector and high-risk AI operators
It is designed for contexts where “we don’t know” is no longer an acceptable answer.
Regulatory Compatibility
Standards & Regulatory Alignment
AI OSI is jurisdiction-agnostic by design.
Its architecture is aligned with:
EU AI Act (including Annex IV documentation requirements)
ISO/IEC 42001
NIST AI Risk Management Framework
Alignment is architectural, not declarative. AI OSI specifies what must be provable — independent of jurisdiction, vendor, or deployment model.
Canonical References
Canonical Briefings & Technical Papers
All documents below are reference-grade materials designed for conformity assessment, assurance work, and standards alignment. They are descriptive, not prescriptive, and do not imply endorsement, adoption, or authority.
Canonical specifications are publicly archived on Zenodo, providing persistent DOIs, independent timestamping, and verifiable version history.
Executive Brief
A concise, high-level overview of the AI OSI Stack, its purpose, architectural principles, and evidence-layer requirements. Designed for board members, regulators, and senior governance stakeholders requiring rapid orientation without technical depth.
Download PDF (5 pages, 81 KB)
The AI OSI Stack: Canonical Specification (v4)
The authoritative reference architecture defining layered governance controls, lifecycle obligations, evidence requirements, AEIP schemas, and conformance expectations for high-stakes AI systems. This canonical edition is archived on Zenodo with a persistent DOI, providing independent publication, versioning, and authorship provenance.
Download PDF (72 pages, 392.6 KB)
EU AI Act Annex IV Alignment Note
A non-binding conformance mapping showing how AI OSI artifacts, evidence structures, and verification models align with EU AI Act Annex IV documentation requirements for high-risk AI systems.
Download PDF (4 pages, 80 KB)
Roadmap & Work Completed
A dated, versioned record of development milestones, publications, submissions, and external evaluation activity. Provided to support transparency, continuity, and institutional diligence.
Download PDF (14 pages, 52 KB)
Role-Specific Executive Briefings (Illustrative)
The following briefings illustrate how the AI OSI architecture applies to specific oversight and accountability roles. They are advisory in nature and do not imply endorsement, adoption, or role authority.
Defensible AI Oversight for Boards & Audit Committees
An executive briefing for directors and audit committees addressing fiduciary exposure, oversight failure modes, and the role of contemporaneous evidence in defending AI-related decisions under regulatory, audit, or legal scrutiny.
Download PDF (3 pages, 75 KB)
Non-Operational AI Governance for CISOs & Cyber Risk Leaders
An executive briefing for cyber risk leaders explaining how AI governance evidence can be established without interfering with security operations, SOC tooling, or incident response workflows.
Download PDF (3 pages, 76 KB)
AI Governance Evidence for Legal & Regulatory Defense
An executive briefing for general counsel and compliance teams focused on discovery-ready evidence, temporal legitimacy, and defensible AI decision records under litigation and enforcement conditions.
Download PDF (3 pages, 76 KB)
Audit-Grade Evidence for Regulators & Oversight Bodies
An executive briefing for regulators, auditors, and programme evaluators describing governance evidence structures that support consistent review, cross-institutional comparison, and longitudinal oversight.
Download PDF (3 pages, 75 KB)
Project Status and Scope
Status, Independence, and Direction
AI OSI is an independent governance architecture initiative.
It is not a regulator, standards body, certification authority, or commercial AI product.
The work is published for evaluation on its architectural and evidentiary merits, independent of institutional affiliation or endorsement.
Inquiry and Correspondence
Contact
Informal, exploratory, and off-the-record conversations are welcome.
Engagement does not imply endorsement, adoption, or public attribution.
Institutional, academic, and public-sector inquiries are encouraged, particularly regarding:
Research collaboration
Pilot deployments
Public-sector or high-risk AI use cases
Funding or fellowship opportunities related to AI governance infrastructure
Email: aiosiproject@gmail.com
Location: Los Angeles, California (PST)
Working internationally and across jurisdictions.
Last updated: December 2025
