MLOps

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MLOps

MLOps (machine-learning operations) is the set of practices for deploying, monitoring, and maintaining machine-learning and AI models reliably in production. It applies DevOps-style discipline — automation, versioning, testing, monitoring — to AI systems.

How it works

MLOps covers the full lifecycle: versioning data and models, automated training and deployment pipelines (CI/CD), and continuous monitoring for performance drift, cost, and safety. For agentic AI, it also includes guardrails, evaluation, and audit trails.

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Why it matters

Most enterprise AI value is lost between pilot and production — only about 39% of organizations attribute any EBIT impact to AI. Mature MLOps is a key differentiator for the minority that do. See Enterprise AI Statistics 2026.