This article explores a novel architecture that combines graph neural networks with Procurize’s AI platform to automatically attribute evidence to questionnaire items, generate dynamic trust scores, and keep compliance responses up‑to‑date as regulatory landscapes evolve. Readers will learn the data model, the inference pipeline, integration points, and practical benefits for security and legal teams.

This article explores the need for responsible AI governance when automating security questionnaire responses in real time. It outlines a practical framework, discusses risk mitigation tactics, and shows how to combine policy‑as‑code, audit trails, and ethical controls to keep AI‑driven answers trustworthy, transparent, and compliant with global regulations.