Every team wants to point AI agents and dashboards at their data and simply trust the answers. The problem is that a model knows the world — but it doesn't know your company. Its output is only ever as good as the data and context you put in front of it.

Agent quality is usually bottlenecked by input quality, not model capability. A weak data and context layer shows up as hallucinations, broken task continuity, wasted tokens, and behaviour nobody can predict. A strong one does the opposite — but building it means someone has to guarantee, before an agent answers a customer or a dashboard drives a decision, that the underlying data is actually fit to be used.

This half-day session covers how modern data teams make data AI-ready — using AI itself to set data contracts, assess quality, and decide what's safe for agents to consume. A discipline-first session built for governance and CDO-level leaders, with Soda's end-to-end approach as the worked example.