Continuous Integration/Continuous Deployment (ML)
The practice of automatically testing, validating and deploying machine learning models and pipelines to ensure rapid, reliable and reproducible updates to production systems.
In plain language
Automating the testing and release of AI model updates so improvements reach production quickly and reliably. Like a factory assembly line for AI models where every change is automatically tested before going live.
Why this matters
CI/CD for ML is essential for managing update risk and maintaining governance over deployed systems. Your implementation framework should require automated testing and validation before any model update reaches production, preventing unwanted drift or degradation.
Relevance
ImplementationAutomated testing and deployment pipelines provide governance assurance over model updates and reduce the risk of unvalidated changes reaching production.
Related terms
Putting continuous integration/continuous deployment (ml) into practice in your organisation?
Ready to transform your AI strategy?
Partner with Australia's AI strategy and governance specialists. From adoption roadmaps to ISO 42001 audit readiness.