An AI Pipeline is a sequence of connected processes that moves data through the stages required to build, deploy, and operate an artificial intelligence system. Depending on its purpose, a pipeline may handle data collection and preparation, feature engineering, model training, evaluation, deployment, and ongoing monitoring.
AI pipelines automate the movement and transformation of data and models between these stages, making complex workflows more repeatable and easier to manage. In production environments, they can incorporate validation, version control, testing, retraining, and deployment triggers, helping teams move AI systems from experimentation to reliable operation with less manual intervention.
