Standard
AI Total Cost of Ownership Governance Standard
This standard governs the full-lifecycle cost of an AI capability as governance evidence. A business case, or a continue-or-retire decision, judged on metered runtime spend alone systematically understates cost, because the costs that make an AI capability's lifecycle total diverge from its provider invoice are the non-metered ones: people, integration, oversight, governance overhead, model succession, and decommission. Recording, owning, and re-forecasting the total lets the cost side of an AI decision be weighed on lifecycle terms.
- Type
- Standard
- Version
- 0.0.7
- Date
- 2026-10-27
- Owner
- AI Governance Approver
- Approving authority
- Governance Library Maintainer
- Classification
- Public
- Confidentiality
- Public
- Category
- AI Governance
- Review frequency
- Annual and upon material AI portfolio, provider-pricing, or sourcing-model change
- Licence
- CC BY-SA 4.0
Read the full text on GitHub (opens in a new tab)
Outline
- 1. Purpose
- 2. Scope
- 3. Principles
- 4. TCO cost taxonomy
- 5. The TCO record
- 6. Non-metered and internal cost requirements
- 7. Lifecycle-stage TCO controls
- 8. TCO in governance decisions
- 9. Reporting
- 10. Framework alignment
- 11. Limitations
Frameworks it maps to
Related documents
- AI Value and Decision-Governance Frameworkai
- AI Inference Cost Governance Standardai
- IT Financial Management Standardoperations
- AI Model Succession and Identity Continuity Standardai
- AI Human-Oversight Standardai
- AI Model Lifecycle Management Procedureai
- Model Registryai
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