Human Review Layers for Validating AI-Generated Financial Models

An AI system can generate a financial spreadsheet that looks correct and gives coherent results while still embedding wrong assumptions, which makes such errors hard to spot. The article argues that spreadsheet quality has several dimensions, including syntax, semantics, input references, and source support, each requiring different controls. It recommends separating interpretation, calculation, validation, and professional approval so each can be tested on its own. The proposed architecture is presented as an educational pattern rather than a description of any specific product. It distinguishes inputs, assumptions, evidence, model outputs, and professional decisions, and routes AI-extracted values through human approval before a deterministic calculation engine and independent checks.