Drata for AI governance: what it covers and what it does not
Side by side.
| Axis | Hael | Drata |
|---|---|---|
| Security compliance automation | Not the product's centre of gravity; Hael covers the AI-governance surface and expects a security-compliance platform alongside it. | Publicly positioned as the Agentic Trust Management Platform, with continuous compliance, integrated internal and third-party risk, and real-time customer assurance across 8,500+ global customers. Source: drata.com — AI |
| AI-specific frameworks supported | EU AI Act, ISO/IEC 42001, NIST AI RMF, GDPR Article 22, Colorado ADMT Act, Texas TRAIGA, NYC LL144, California ADMT, Illinois HB 3773, Utah AI Policy Act, Korea AI Basic Act — with per-framework readiness tooling and cited briefs. | Publicly lists ISO/IEC 42001 and the NIST AI RMF among 30+ pre-built frameworks; broader AI-specific regulatory coverage (EU AI Act artefacts, US state AI laws) is not itemised on the public frameworks page. Source: drata.com — Frameworks |
| Regulatory artefact generation | Generates Annex IV files, model cards, impact assessments and technical documentation from the live governance record. | Not publicly documented. ISO 42001 is offered as a pre-built framework with control mapping; generation of EU AI Act technical files or system-level model cards is not described on the public product pages. Source: drata.com — Frameworks |
| Agent governance | Agent registry, per-agent lifecycle state, tool-use policy, human-in-the-loop gates and tamper-evident audit chain. | Not publicly documented as a runtime control surface for AI agents. Drata AI is publicly positioned as intelligence embedded across compliance, risk and assurance workflows (faster answers, faster reviews, faster remediation), which is a different product concern. Source: drata.com — AI |
| AI questionnaire answering | Answers inbound AI questionnaires from the same record that runs governance — evidence-cited answers, one canonical library, coordinator workflow. | Publicly cites faster questionnaire answers as part of Drata AI, framed as a security/GRC assurance surface rather than an AI-specific diligence surface. Source: drata.com — AI |
| Trust centre | Public trust centre generated from the same governance record — model summaries, framework posture, sub-processors, incidents and change notice. | Publicly offers a Trust Center product to show compliance externally, positioned around security frameworks rather than AI-system disclosures. Source: drata.com — Frameworks |
| Target buyer | AI-native vendors and regulated enterprises where the same team must produce the evidence, answer the questionnaire and run the controls. | Publicly cites 8,500+ global customers across security compliance, with a 4.8/5.0 G2 rating referenced on its AI product page. Source: drata.com — AI |
| Pricing transparency | Public pricing page with tier structure; enterprise terms available on request. | Not publicly documented. Pricing is quoted via sales; no public price page is published as of the dateline. Source: drata.com |
What Drata genuinely covers
The security compliance layer is table stakes for any vendor, and Drata automates it credibly: it publicly positions itself as the Agentic Trust Management Platform, with continuous compliance, integrated internal and third-party risk, and real-time customer assurance across more than 8,500 global customers (https://drata.com/platform, https://drata.com/products/ai). Its frameworks page cites 30+ pre-built frameworks, including SOC 2, ISO 27001, HIPAA, PCI DSS, FedRAMP, HITRUST, NIS 2 and DORA, with continuous control monitoring and a Trust Center surface for external assurance (https://drata.com/product/frameworks). For AI-adjacent standards, Drata publicly lists ISO/IEC 42001 ("Govern responsible AI with a standardized management system") and the NIST AI RMF as pre-built frameworks in that same catalogue.
Where AI governance goes beyond it
AI diligence asks questions security compliance was never designed to answer: the risk classification of a system in the buyer's use, the technical documentation behind it, training data provenance, evaluation results, oversight design, and what happens when the model misbehaves. Those attach to systems, not to the company, and they require artefacts generated from how each system actually operates. A SOC 2 report, however clean, answers none of them, which is why AI sections now appear in questionnaires alongside the security sections Drata already handles.
Running both
The practical pattern for an AI vendor selling to enterprise: Drata (or equivalent) for the security layer, a system-of-record for the AI layer, and one consistency discipline across both, because the buyer reads them side by side.
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