Everyone wants you to "add AI." Nobody can tell you where it belongs — or where it will quietly make things worse.

The situation

There’s pressure to “do something with AI,” and a graveyard of proofs-of-concept that never reached production because the data underneath wasn’t ready, the cost was unbounded, or nobody could evaluate whether the output was any good. The technology is the easy part; the architecture around it is where these efforts live or die.

What Enablement does

I separate the genuine opportunities from the hype, assess whether your data is actually ready to support them, and then build one use case properly — with evaluation, cost controls, and a reference pattern your team can reuse.

What you walk away with

• An opportunity map that tells you where to invest and, just as usefully, where not to.
• A reference architecture for AI features that fits your existing stack — Unity Catalog, dbt, MCP, and all.
• One production-grade use case shipped, with the guardrails to run it safely.