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The CISO's Guide to Buying AI

Learn what CISOs should evaluate before buying from AI vendors

This guide is built for CISOs navigating the AI buyer market who want to ask vendors the right questions and understand if the AI tools they are reviewing are going to produce meaningful results.

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100+

Darktrace resources dowloaded in last 30 days

92%

of security professionals say they need to understand how defensive AI tools make decisions before they can trust them

14%

of security professionals allow AI to take fully autonomous remedial action without human approval

74%

of security professionals are limiting AI autonomy in the SOC until explainability improves

89%

of security professionals say they have visibility into the reasoning behind AI-generated outputs

What's inside this resource

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Understand how to assess AI governance frameworks, certifications, compliance practices, and safeguards that help ensure AI systems are secure, reliable, and responsibly managed.

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Governance and AI safety controls

Understand how to assess AI governance frameworks, certifications, compliance practices, and safeguards that help ensure AI systems are secure, reliable, and responsibly managed.

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Learn why training data quality, model selection, testing workflows, and continuous validation directly impact AI accuracy, resilience, and long-term operational performance.

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How AI models are trained and validated

Learn why training data quality, model selection, testing workflows, and continuous validation directly impact AI accuracy, resilience, and long-term operational performance.

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Explore the governance, validation, explainability, and testing practices that determine whether an AI system can be trusted to operate safely inside real enterprise environments.

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Understand what drives trustworthy AI

Explore the governance, validation, explainability, and testing practices that determine whether an AI system can be trusted to operate safely inside real enterprise environments.

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Unlock the insights

White Paper

The CISO's Guide to Buying AI

AI Governance, Risk, and Compliance: What to Ask Before You Buy

Only 37% of organizations have an AI governance policy — yet nearly every security vendor now ships AI. That gap is where AI compliance risk lives.

Why AI vendor due diligence requires a deeper look

AI is reshaping security operations, promising faster investigations and stronger detection. But evaluating AI security tools is far more complex than comparing feature lists. Beneath the surface, vendors rely on vastly different models, training methods, governance practices, and validation processes — all of which determine how accurate, trustworthy, and secure a system is in production. For security leaders, understanding how an AI system is built and governed now matters as much as what it does.

The AI governance frameworks that matter

Ask which AI governance framework a vendor actually operates under. ISO/IEC 42001 — the world's first AI management system standard — is externally audited rather than self-claimed, which distinguishes it from frameworks like the NIST AI Risk Management Framework where adherence is often self-asserted. Darktrace is certified to ISO/IEC 42001.

Five categories for AI risk and compliance evaluation

The guide structures AI governance, risk, and compliance due diligence across five areas:

Governance, safety, and data controls — certifications, data ring-fencing, resilience to data poisoning and adversarial inputs
Data gathering and training — provenance, bias prevention, de-identification of PII
Model and technique choice — LLMs, DSLMs, generative, agentic, and composite AI
Performance and accuracy validation — TEVV workflows, model and data drift
Interpretability, adjustability, and transparency — explainable outputs and SOC-level tuning

Your AI vendor due diligence checklist

Includes 17 questions to put to any AI service provider — plus guidance on reading their answers, and why "agentic AI" means something different at every vendor.

Download the guide for the full AI vendor due diligence checklist.