Executive Assessment Tool

CTO Data Readiness Audit
Before You Buy AI

Three diagnostic questions reveal whether your data architecture is ready to support AI — or whether you're about to build on a cracked foundation.

⏱ 5 minutes
Question 01 of 03
Have your critical data sources experienced schema drift for three or more years?
Schema drift happens when columns get added, renamed, or repurposed over time without formal governance. After three years it compounds — and AI can't learn from a moving target.
Question 02 of 03
Do basic business questions take longer than five seconds to answer?
Query latency is a proxy for architectural health. If business questions require ETL runs, data team intervention, or manual joins, your gold layer isn't working for you.
Question 03 of 03
Are your data teams spending more than 50% of their time on ETL instead of analysis?
When your best data minds are plumbers, you're not doing data work — you're doing data maintenance. AI amplifies analysis; it can't rescue teams trapped in pipeline work.
out of 3
critical issues flagged

Have your critical data sources experienced schema drift for 3+ years? Persistent schema changes lead to inconsistencies and AI comprehension failures.

Yes
Partially
No

Do basic business questions take longer than 5 seconds to answer? Slow response times signal infrastructure or governance problems.

Yes
Mixed
No

Are your data teams spending more than 50% of their time on ETL instead of actual analysis? A disproportionate ETL burden signals infrastructure debt.

Yes
~50/50
No
out of 3
critical issues flagged