A structured 62-question vendor assessment questionnaire across 8 security domains that CISOs and procurement teams use to evaluate AI vendors before onboarding. Covers data privacy, security architecture, model transparency, compliance certifications, incident response, contractual protections, business continuity, and audit rights.
A 62-question security questionnaire for evaluating AI vendors across 8 assessment domains. Covers data privacy, security architecture, model transparency, compliance, and contractual protections.
73% of organisations experienced a security incident originating from a third-party vendor in 2025, yet only 28% have AI-specific questions in their vendor assessment process - leaving the fastest-growing attack surface almost entirely unexamined during procurement.
This 62-question questionnaire covers 8 critical assessment domains - data privacy, security architecture, model transparency, compliance, incident response, legal protections, business continuity, and audit rights - giving procurement teams a single, standardised instrument for every AI vendor evaluation.
AI vendor contracts without explicit training data opt-out clauses expose your organisation to intellectual property leakage; 41% of AI vendors reserve the right to use customer inputs for model improvement unless contractually prohibited, making Section 6 (Contractual Protections) the most frequently overlooked yet highest-impact domain.
The EU AI Act (effective August 2025) and the NIST AI RMF impose specific obligations on organisations deploying third-party AI systems - this questionnaire maps vendor responses directly to compliance requirements across GDPR, SOC 2, ISO 27001, HIPAA, and the EU AI Act so you can demonstrate due diligence to auditors.
Organisations using structured AI vendor risk assessments reduce vendor-related security incidents by 64% and cut onboarding timelines by 40% compared to ad-hoc evaluation processes, according to Gartner's 2025 Third-Party Risk Management survey.
62 structured security questions across 8 assessment domains to evaluate AI vendors before onboarding.
Assess how the AI vendor collects, processes, stores, and retains your data. These questions determine whether vendor data handling practices meet your organisation's privacy requirements.
Evaluate the vendor's security infrastructure, encryption standards, access controls, and vulnerability management practices.
Ensure every AI vendor meets enterprise security standards before deployment, and maintain a defensible due diligence record for regulators and board reporting
Standardise the AI vendor evaluation process with a repeatable questionnaire that procurement teams can issue without needing deep technical security expertise
Map vendor capabilities to regulatory requirements across GDPR, EU AI Act, SOC 2, HIPAA, and ISO 27001 - and document compliance gaps before contract execution
Evaluate AI vendor architecture, data handling practices, and model transparency to ensure technical compatibility with enterprise security requirements
Assess contractual protections, data processing agreements, liability clauses, and IP ownership terms before signing AI vendor contracts
Sections 1 and 4 include HIPAA-specific questions on PHI processing, BAA requirements, and minimum necessary access controls for AI systems. Healthcare organisations must verify that AI vendors can execute a BAA covering AI-specific processing scenarios before any patient data enters the platform.
Sections 2 and 4 address SOC 2 Trust Services Criteria, encryption standards, and access controls critical for financial institutions. Section 7 covers business continuity requirements aligned with DORA operational resilience mandates for AI-dependent financial workflows.
Sections 3 and 6 are essential for law firms evaluating AI vendors for document review, research, or drafting. Model explainability, IP ownership of AI outputs, and confidentiality protections must be contractually guaranteed before any client-privileged data is processed.
Sections 4 and 8 align with NIST AI RMF Govern and Manage functions and FedRAMP security control requirements. Government agencies and contractors must verify that AI vendors meet federal security standards, including data sovereignty, cleared personnel requirements, and continuous monitoring obligations.
Assess how the AI vendor collects, processes, stores, and retains your data. These questions determine whether vendor data handling practices meet your organisation's privacy requirements and regulatory obligations.
Evaluate the vendor's security infrastructure, encryption standards, access controls, and vulnerability management practices to determine if they meet enterprise-grade security requirements.
Understand how the vendor's AI models work, how outputs are generated, and what safeguards exist against bias, hallucination, and unreliable outputs. Critical for regulated industries where explainability is mandatory.
Verify the vendor's compliance posture across relevant regulatory frameworks. Determine whether their certifications, audit reports, and compliance practices align with your organisation's requirements.
Take our 2-minute assessment and get a personalised AI governance readiness report with specific recommendations for your organisation.
Start Free AssessmentAssess the vendor's ability to detect, respond to, and communicate about security incidents. AI-specific incidents - including data leakage through prompts, model manipulation, and training data poisoning - require specialised response procedures.
Evaluate the legal and contractual safeguards that protect your organisation's data, intellectual property, and liability exposure when using the vendor's AI platform.
Evaluate the vendor's availability guarantees, disaster recovery capabilities, and data portability provisions to ensure your organisation is not exposed to operational risk or trapped in a vendor relationship.
Establish your organisation's rights to continuously monitor the vendor's security posture, conduct audits, and verify ongoing compliance. Effective third-party risk management requires visibility beyond the initial assessment.
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A step-by-step framework for creating an AI governance program in a mid-market organization. Covers stakeholder alignment, policy development, tool selection, deployment, compliance mapping, and measurement with a 90-day implementation timeline.
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“This framework saved us 3 months of policy development. We went from zero AI governance to audit-ready in under 2 weeks.”
— Security Leader, Mid-Market Healthcare Organisation
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