Snowflake CoCo

Global – October 27, 2026 -- Snowflake's sales finance team has cut its monthly forecast and variance analysis from more than a week to a few hours. It did so by giving its CoCo AI standing context about company data, terminology and workflows.

Profile cuts steps per answer from 3.0 to 1.3

Across 44 finance users, those with a 'GTM Finance' profile reached an answer in about 1.3 steps, against about 3 steps for those without one (Snowflake internal CoCo usage, February to May 2026). Without the profile, the AI spent roughly three steps per session finding the right data source and resolving terminology.

Each extra step adds about 0.05 credits, roughly 10 cents at US$2 per credit. A five-step session therefore costs about three and a half times a one-step session. At every step count in the data, sessions with the profile cost less than those without.

North America – October 27, 2026 -- Snowflake's product data science team cut the time from pipeline incident to a tested, reviewable fix to under 16 minutes using its CoCo agentic AI assistant. Before CoCo, diagnosis took a skilled engineer about 30 minutes per case. The result comes from a four-part framework that Snowflake built to measure AI value beyond license counts and prompt volumes.

Snowflake sorts AI work into three levels instead of counting prompts

Dashboards built on access and activity score an organization running 1,000 explanations the same as one running 1,000 pipeline builds and anomaly investigations. Snowflake's framework separates foundational work (explaining code, answering questions), applied development (writing code, exploring data, building reports) and agentic work (multistep processes where AI uses tools to finish an outcome). Real capacity gains should appear in the agentic tier.