What breaks when we add AI to an existing data platform?
Data Platform AI Readiness Assessment
Adding LLM capabilities to Databricks, Snowflake, BigQuery, or similar platforms introduces new control requirements that existing data governance may not address.
Why This Question Matters
Data teams often have mature governance for analytics—but AI workloads change the threat model. Embeddings, vector stores, model training, and inference introduce data flows that bypass existing controls. Teams that assess AI readiness early avoid retrofitting security after production incidents.
What the Output Will Cover
This output will map: data flow changes from AI workloads, model access and versioning requirements, vector store governance, prompt/response boundaries, and inference isolation. You will receive a reference architecture showing how AI layers interact with existing data platform controls.
Before You Begin
- • This assessment takes approximately 5 minutes
- • You will receive a shareable reference architecture
- • No vendor recommendations or product comparisons are included
- • All outputs state explicit assumptions and limitations