AI-ready metadata reduces query failures by making ownership, freshness, lineage, quality, and policy visible at execution time.
Autonomous materialization is useful when it is tied to workload evidence, governance checks, and lifecycle management.
AI agents need more than metric names. They need composable business logic that survives multi-step analysis.
Dremio Agentic Lakehouse is easiest to understand as two ideas: data built for agent access and platform work managed by agents.
