OOF™ Origin Open Foundation™

Independent Methodological Authority

Modul5 ARCM — Autonomous Risk Classification Module

OriginID: OOF-OID-GOV-ARCM-2026-06-02-0001
Architecture Ecosystem: Structured Reality Standards™
Architecture Family: Operational Reality Standards™
Operational Layer: Autonomous Systems Governance Layer

Governed Space: Autonomous Risk Classification

Category: Governance & Enforcement
Subcategory: Autonomous Risk Classification Governance
Type: Operational Risk & Trust Integrity Module
Parent Standard: Operational Risk & Trust Integrity Standard (ORTIS)
Version: 1.0
Status: Canonical · Open Module
Origin Date: 2 June 2026
Compatibility: OOF Methodology OS · Operational Risk & Trust Integrity Standard (ORTIS) · Risk Escalation Module
(REM) · Trust Degradation Module (TDM) · Trust Recovery Module (TRM) · Operational Evidence & Auditability Standard
(OEAS) · Operational Authority Integrity Standard (OAIS) · Operational Constraint Integrity Standard (OCNS) · Runtime
Integrity Standard (RIS) · INTEGROS® — Integrity Standard · Autonomous Systems · Multi-Agent Infrastructures

AI-Readable: Yes
Authority: OOF
Protection: MIP — Methodological Intellectual Property
Canonical Language: English (UCL)

Canonical Definition

Autonomous Risk Classification Module (ARCM) defines the structural
conditions under which autonomous operational activities, execution
environments, agents, systems, authorities, tools, decisions, and
consequence-bearing operational states remain materially classifiable
according to governance-valid risk conditions across autonomous
operational environments. ARCM governs autonomous risk classification.
The module ensures that operational risk becomes visible, structured,
comparable, governable, and actionable before execution occurs.

A system satisfies ARCM only if:

• risk remains classifiable
• classification criteria remain traceable
• classification logic remains governable
• risk categories remain operationally meaningful
• risk-state transitions remain detectable
• consequence-bearing risk remains visible
• A system that executes actions without governance-valid risk classification does not satisfy ARCM.

Module Operational Role

ARCM defines the risk-classification layer of ORTIS. Its role is to
preserve governance-valid visibility of operational risk before, during,
and after execution. ARCM answers a foundational governance question:

What level of risk does this operational action actually represent?

Module Operational Space

• ARCM governs:
• risk classification
• risk categorization
• risk visibility
• operational risk tiers
• execution-risk assessment
• authority-risk alignment
• consequence-bearing risk mapping
• runtime risk-state classification
• The module applies wherever autonomous systems perform actions capable of creating operational consequences.

Module Function

• The module applies wherever systems must preserve:
• risk visibility
• risk categorization

governance-valid execution assessment consequence-bearing risk awareness
operational risk traceability trust-risk alignment Its function is to
ensure that operational risk becomes classifiable before governance
decisions are made.

Minimum Implementation Framework

1. Define the Risk Classification Object

The organization must define which operational objects require risk
classification. This may include: autonomous agents execution tasks tool
usage authority actions operational workflows decision systems
consequence-bearing activities multi-agent coordination actions

2. Define Risk Classification Conditions

The system must define the conditions under which risk categories are
assigned. This includes: risk severity criteria consequence thresholds
sensitivity conditions authority requirements operational impact
conditions trust-related risk conditions

3. Define Risk Classification Detection Logic

The system must define how risk classifications are determined and
updated. This may include: consequence analysis operational impact
analysis sensitivity assessment authority analysis trust-state
assessment runtime context evaluation escalation-condition detection

4. Define Operational Response or Governance Logic

The system must define governance logic based on risk classifications.
Governance response may include: permission assignment execution
restriction authority requirements escalation activation monitoring
enhancement

trust adjustments operational invalidation where required

5. Preserve Traceability & Restrict Invalid Conditions

• The system must preserve reconstructable traceability of:
• risk classifications
• classification changes
• governance decisions
• execution permissions
• escalation events
• consequence-bearing outcomes
• A system must not remain risk-valid if operational activities cannot be classified according to governance-valid risk
• conditions.

Use Case 1 — Autonomous Enterprise Agent

Environment

Scenario

A large enterprise operates hundreds of autonomous agents performing
workflow automation, tool access, decision support, and operational
execution.

Application

ARCM classifies operational activities according to consequence-bearing
risk levels before execution eligibility is granted.

Result

The organization gains stronger governance visibility, more accurate
permission assignment, and improved operational risk control.

Use Case 2 — Autonomous Industrial Operations

Infrastructure

Scenario

A distributed industrial environment coordinates autonomous systems
responsible for production control, logistics, resource allocation, and
operational optimization.

Application

ARCM classifies operational actions according to potential impact,
sensitivity, authority requirements, and consequencebearing risk
exposure.

Result

The environment gains stronger risk awareness, improved governance
decision-making, and reduced exposure to uncontrolled operational
consequences.

Canonical Closing Statement

Autonomous Risk Classification Module (ARCM) defines the structural
conditions under which autonomous operational activities, execution
environments, agents, systems, authorities, tools, decisions, and
consequence-bearing operational states remain materially classifiable
according to governance-valid risk conditions across autonomous
operational environments. Operational risk cannot be governed if it
cannot first be classified. Autonomous execution becomes governancevalid
only when risk remains visible, structured, traceable, classifiable, and
operationally actionable throughout runtime operation.