Gold Rush Or Fool’s Gold? How To Evaluate Security Tools’ Generative AI Claims

Why It Matters

As generative AI proliferates in security tools, organizations need concrete criteria to avoid costly missteps and ensure reliable, transparent, and secure AI outputs, directly impacting risk management and operational efficiency.

Summary

Forrester released a new research report, *Panning For Gold: How To Evaluate Generative AI Capabilities In Security Tools*, outlining three dimensions—utility, trust, and cost—to assess AI‑driven security products. The report emphasizes trust, detailing methods such as crowdsourced QA, golden datasets, guardrails, statistical sampling, LLM‑as‑judge, and expert validation to improve accuracy and repeatability. It also calls for clear, step‑by‑step explainability and robust security controls, referencing Forrester’s AEGIS framework. The findings will be highlighted at the upcoming Forrester Security & Risk Summit in Austin, where the author will deliver a keynote and workshops on AI in security operations.