OriginID: OOF-OID-ASGA-ARTS-ORCM-2026-07-06-0001
Architecture Ecosystem: Structured Reality Standards™
Architecture Family: Autonomous Systems Governance Architecture
(ASGA™)
Operational Layer: Autonomous Operational Governance Layer
Governed Space: Operational Risk Classification
Category: Governance & Enforcement
Subcategory: Autonomous Operational Governance
Type: Autonomous Risk & Trust Standard Module
Parent Standard: Autonomous Risk & Trust Standard (ARTS)
Version: 1.0
Status: Canonical · Open Module
Origin Date: 6 July 2026
Compatibility: OOF Methodology OS · GOA™ · ORA™ · AGA™ · AIG® ·
CLIA® · MGIA™
AI-Readable: Yes
Authority: OOF®
Protection: MIP™ — Methodological Intellectual Property
Canonical Language: English (UCL)

Canonical Definition

Operational Risk Classification Module (ORCM) defines the structural
conditions under which autonomous operational risks are identified,
classified, prioritized, and governed before and during autonomous
operation.

ORCM governs operational risk classification.

The module establishes the governance conditions required to ensure
that autonomous operational risks are consistently evaluated
according to their potential impact, likelihood, and operational
significance.

Risk cannot be governed until it is classified.

ORCM governs that classification.

Module Operational Role

ORCM defines the operational risk classification layer of ARTS.

Its role is to establish a consistent governance framework for
identifying and classifying operational risks throughout autonomous
operation.

Module Operational Space

ORCM governs:

• operational risk classification,
• risk identification,
• risk categorization,
• operational risk prioritization,
• governance risk assessment,
• risk severity classification,
• operational risk governance,
• continuous risk evaluation.

Module Function

The module applies wherever organizations must identify and classify
autonomous operational risks before and throughout autonomous
execution.

Minimum Implementation Framework

1. Define the Risk Classification Object

Identify which autonomous operational activities require risk
classification.

2. Define Classification Conditions

Establish governance conditions for identifying, categorizing, and
prioritizing operational risks.

3. Define Classification Failure Logic

Identify conditions where risk classification becomes incomplete,
inaccurate, inconsistent, or governance-invalid.

4. Define Governance Response

Define governance actions for risk acceptance, mitigation,
escalation, reassessment, or operational restriction.

5. Preserve Risk Traceability

Preserve risk classifications, governance decisions, operational
evidence, reassessment history, and supporting documentation.

Use Case 1 — Autonomous Cargo Drone

Scenario

An autonomous cargo drone prepares to operate under changing weather
conditions.

Application

ORCM classifies operational risks before mission execution and
adjusts governance requirements accordingly.

Result

The mission proceeds with risk awareness, appropriate operational
controls, and governance oversight.

Use Case 2 — Autonomous Healthcare Robot

Scenario

An autonomous clinical robot performs patient-support activities
within a hospital.

Application

ORCM continuously classifies operational risks associated with
patient interaction and clinical procedures.

Result

Healthcare operations remain aligned with governance requirements
and acceptable operational risk levels.

Canonical Closing Statement

Governable autonomy begins with governable risk understanding.
Operational Risk Classification ensures that autonomous operational
risks are consistently identified, prioritized, and governed before
they become operational failures.

→ Autonomous Risk & Trust Standard (ARTS)