This article explores a novel, ontology‑driven prompt engineering architecture that aligns disparate security questionnaire frameworks such as [SOC 2](https://secureframe.com/hub/soc-2/what-is-soc-2), [ISO 27001](https://www.iso.org/standard/27001), and [GDPR](https://gdpr.eu/). By building a dynamic knowledge graph of regulatory concepts and leveraging smart prompt templates, organizations can generate consistent, auditable AI answers across multiple standards, reduce manual effort, and improve compliance confidence.

In an environment where vendors face dozens of security questionnaires across frameworks such as [SOC 2](https://secureframe.com/hub/soc-2/what-is-soc-2), [ISO 27001](https://www.iso.org/standard/27001), GDPR and CCPA, generating precise, context‑aware evidence quickly is a major bottleneck. This article introduces an ontology‑guided generative AI architecture that transforms policy documents, control artifacts and incident logs into tailored evidence snippets for each regulatory question. By coupling a domain‑specific knowledge graph with prompt‑engineered large language models, security teams achieve real‑time, auditable responses while maintaining compliance integrity and reducing turnaround time dramatically.