AI amplifies your data — good or bad
AI tools don’t fix messy data; they amplify whatever you give them. Feed them inconsistent, scattered records and you’ll get confident-sounding answers built on shaky ground. Readiness starts well before you choose a tool.
The groundwork that matters
Practical AI readiness looks a lot like good data hygiene: consistent structure, clear definitions, deduplicated records, and a single trusted source for the data you care about. Get that right and most AI tools become dramatically more useful.
Start small and low-risk
You don’t need a sweeping AI strategy to begin. Pick one well-understood, well-structured dataset and a concrete question, then build from there. A pragmatic, low-risk first step beats an ambitious project on top of unprepared data.