Overview
The ISO 55000 series provides the international standard for asset management systems, establishing principles, requirements, and guidance for organizations that depend on physical, financial, information, and intangible assets to achieve their objectives. Updated significantly in 2024, the series is particularly relevant for asset-intensive industries including utilities, transportation, manufacturing, and public infrastructure.
Utilities are already ISO 55000 shops—early adopters through PAS 55. The 2024 update includes ISO 55013 on Data Asset Management, creating a natural bridge: "You already do asset management governance—extend it to AI."
The ISO 55000 Family (2024)
Core Standards
| Standard | Title | Purpose |
|---|---|---|
| ISO 55000:2024 | Vocabulary, Overview, Principles | Foundational concepts |
| ISO 55001:2024 | Requirements | Certifiable management system |
| ISO 55002:2018 | Guidelines for Application | Implementation guidance |
Supporting Standards (2024 Releases)
| Standard | Focus | AI Relevance |
|---|---|---|
| ISO/TS 55010:2024 | Financial Alignment | AI investment justification |
| ISO 55011:2024 | Government Policy | Public sector AI governance |
| ISO 55012:2024 | People Involvement | AI skills and competency |
| ISO 55013:2024 | Data Asset Management | Critical for AI/data governance |
Core Principles
| Principle | Description | AI Governance Connection |
|---|---|---|
| Value | Assets exist to provide value | AI systems must demonstrably contribute value |
| Alignment | Convert strategy to decisions | AI initiatives align with organizational strategy |
| Leadership | Culture and accountability | CAIO role parallels asset management sponsorship |
| Assurance | Assets fulfill their purpose | AI validation, monitoring, and audit |
ISO 55013:2024 — Data Asset Management
The new ISO 55013 standard is particularly relevant for AI governance:
- Data Asset Strategy: Managing training data as organizational assets
- Data Lifecycle: Governing AI model data throughout lifecycle
- Data Quality: Quality requirements for AI training data
- Integration: Connecting data governance with AI governance
Industry Applications
Utilities (Electric, Gas, Water)
Adoption: High—early adopters through PAS 55
- Grid infrastructure lifecycle management
- Predictive maintenance using AI
- Regulatory compliance (NERC CIP, state PUC)
- AI opportunities: maintenance scheduling, failure prediction, grid optimization
Transportation
Adoption: Growing across rail, aviation, highways
- Infrastructure condition assessment
- Capital investment prioritization
- AI opportunities: autonomous vehicles, predictive maintenance, traffic optimization
Integration with AI Governance
Organizations with mature ISO 55001 implementations can extend their asset management system to cover AI:
| ISO 55001 Element | AI Governance Parallel |
|---|---|
| Asset Management Policy | AI Governance Policy |
| Strategic Asset Management Plan | AI Strategy and Roadmap |
| Asset Management Objectives | AI Objectives and Metrics |
| Risk Assessment | AI Risk Assessment |
| Lifecycle Management | AI Model Lifecycle Management |
| Performance Evaluation | AI Performance Monitoring |