decommission
This glossary entry explains decommission for AI governance and model risk programs. The sections below summarize what the term means in plain language, why chief AI officers and cross-functional committees track it, where teams often get confused, and—when you are signed in—how it shows up across major industries and in expectations tied to the EU AI Act and NIST AI RMF. Use related links at the end of the page to explore neighboring concepts without losing context.
What It Means
Decommission means properly shutting down and removing AI systems, applications, or infrastructure components from your production environment when they're no longer needed. It involves safely disconnecting all dependencies, archiving or deleting data, and ensuring no security vulnerabilities are left behind while maximizing any cost savings from the removal.
Why Chief AI Officers Care
Poor decommissioning creates ongoing security risks from abandoned systems that still have access to sensitive data or network resources. It also wastes money through continued licensing, maintenance, and infrastructure costs for systems that provide no business value. Proper decommissioning ensures compliance with data retention policies and prevents costly security incidents from forgotten legacy systems.
Real-World Example
A retail company built a custom AI recommendation engine three years ago but recently moved to a vendor solution that works better. Decommissioning means shutting down the old system's servers, canceling cloud subscriptions, archiving the customer data according to privacy policies, removing API connections that other systems might still be calling, and ensuring no login credentials or database connections remain active.
Common Confusion
People often think decommissioning just means turning something off, but it's actually a structured process that requires careful planning to avoid breaking dependent systems. It's also confused with deprecation, which is announcing that something will be removed in the future, while decommissioning is the actual removal process.
Industry-Specific Applications
See how this term applies to healthcare, finance, manufacturing, government, tech, and insurance.
Healthcare: In healthcare, decommissioning AI systems requires careful adherence to HIPAA data retention and destruction requirement...
Finance: In finance, decommissioning AI systems requires strict adherence to data retention policies under regulations like SOX, ...
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Includes:
- 6 industry-specific applications
- Relevant regulations by sector
- Real compliance scenarios
- Implementation guidance
Technical Definitions
NISTNational Institute of Standards and Technology
"the total or partial removal of existing components and their corresponding sub-components from Production and any relevant environment, minimizing risks and impacts, ensuring policy compliance, and maximizing the financial benefits (i.e., optimizing the cost reduction). "Source: IG1190M_AIOps_Decommission_v1.0.0
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