AI
Why AI for finance starts with structured data
Everyone is talking about AI for CFOs. But no model is better than the data it gets. Here is why the groundwork decides everything.
AI for finance promises automated forecasts, anomaly detection and natural-language reporting. But every pilot we have seen has stalled on the same thing: messy, unstructured data.
The model is never the problem
Large language models and forecasting algorithms are commodities today. The difference between a valuable AI use case and a demo that never reaches production is the data quality underneath.
What structured data means in practice
- A chart of accounts followed across all entities
- Consistent customer and product dimensions
- Time series without gaps
- Defined KPI formulas
Start here, not there
Before you procure an AI tool — make sure your finance data is consolidated, validated and versioned. That is when AI starts delivering business value.
