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AI Operations

Definition

AI operations refers to the practices used to deploy, monitor, maintain, and improve AI systems in real business environments.

AI operations is the discipline of making AI work after the demo. It includes deployment, monitoring, evaluation, incident handling, cost control, model updates, prompt management, data pipelines, access controls, and continuous improvement.

For Growth Marshal's audience, this is where many companies fail. They buy a tool, run a pilot, get excited, and then nobody owns the system. AI operations gives the business a way to treat AI as infrastructure instead of a weekend experiment.

Related terms

AI Reliability

AI reliability is the degree to which an AI system performs consistently, accurately, and safely under real operating conditions.

Agent Evaluation

Agent evaluation is the process of testing and measuring whether agents perform tasks correctly, safely, and consistently.

LLMOps

LLMOps is the operational discipline for deploying, monitoring, evaluating, and improving large-language-model applications.

MLOps

MLOps is the practice of managing machine learning models through development, deployment, monitoring, and maintenance.