Service 01 · AI & Data Readiness
AI & Data Readiness Assessment
Before you invest in AI, know whether your data can actually support it — a structured assessment of your data foundation against what real AI workloads demand.
Why it matters
Most enterprise AI stalls not on models, but on data: fragmented sources, unclear ownership, gaps in quality and lineage. The result is pilots that never reach production — and budget spent proving what a readiness check would have shown up front.
What I do
Data foundation review
Quality, lineage, ownership, and access across the data your priority use-cases actually depend on.
Governance & compliance check
Is the data governed enough to use safely — privacy, data-protection law, consent, and audit trails in place?
Architecture & access
Can the data actually reach your models at the freshness and scale AI workloads demand?
Readiness scoring & gaps
A clear, scored picture of what is ready, what is not, and what to fix first.
What you get
- A readiness scorecard across data, governance, and architecture
- A prioritised remediation roadmap — what to fix, in what order
- A go / no-go view per AI use-case, with the economics attached
Who it’s for: leaders about to invest in AI who want to de-risk the spend, and teams whose pilots aren’t reaching production.
Where Green Data and Aiconomica meet
This assessment is the bridge between the two practices. Green Data builds the governed-data foundation; this readiness check tells you when it is ready to carry AI — so the two move in parallel, not in sequence.