Super Intelligence definition proposal due (60 days) · Nov 28, 2026 · See what changes
The end-to-end sequence of steps that transforms raw inputs into final AI-generated outputs, including data ingestion, preprocessing, model inference, post-processing, and delivery to end users. In production systems, an AI pipeline may involve multiple models, tools, APIs, and human review checkpoints working in sequence. Governing an AI pipeline means mapping each step: where does data come from, which models touch it, what can go wrong at each stage, and where is the human-in-the-loop?
Why this matters for your team
Map every AI pipeline before it goes to production — data source, each model step, human review points, and output destination. This map is your governance artifact: it shows where errors can enter and who is accountable at each stage.
A content team's AI pipeline: web scraping → topic classification model → draft generation (LLM) → human editor review → publish. Each step is a governance checkpoint.