Data Readiness: Can You Build on This?
Five diagnostic questions that reveal whether your data infrastructure can support the AI-native workflow you're planning to build. Most organisations fail. That's the starting point, not the end.
The Data Tax
The accumulated cost of decades of underinvestment in data infrastructure. Inconsistent schemas. Siloed systems. Missing metadata. Duplicate records. The agents are only as good as the data they process — if the data is garbage, the agents will produce confident, consistent, auditable garbage at machine speed.
The customer ID problem: Sales used the CRM record number. Finance used the billing account number. Customer Service used the email address. The agents created three separate customer profiles for the same person.
Data Readiness Scorecard
Answer each question for your beachhead workflow. Be honest — nobody's watching, and "no" is the most common answer.
The Data Sprint
Not a company-wide data transformation. A targeted intervention for one workflow's data dependencies. Four to eight weeks. The insurance company's sprint cost approximately $180K total — and prevented $2 million in debugging failures.
Most organisations will fail their first Data Readiness Assessment. Not because they're behind — because nearly everyone is behind. The Data Tax is the industry's dirty secret. $180K feels expensive — until you compare it to the $2 million you'll spend debugging agent failures caused by bad data.
The AI-Native Playbook, Chapter 6