AI Decisions Fail Without Business Context

The article uses the story of Maya to argue that the main risk in AI is not model capability but missing context. It outlines seven principles for building a durable advantage, stressing that context must be relevant, precise, shared, governed, owned, and compounding. The key insight is that no single department's context is enough; the full situation requires connected enterprise data.

The article recommends building the context layer in a governed data foundation, such as Snowflake's platform, rather than inside a model or marketing application. Building inside a model creates dependency, while distributing across applications leads to inconsistent definitions. Snowflake positions itself as the neutral home where meaning stays consistent and learning accumulates. However, the article also notes that Snowflake cannot decide what a business should learn—that responsibility remains with the company's marketing and other teams.