Evaluating AI Vendor Security: A Checklist for Procurement and IT Teams
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Evaluating AI vendor security requires a systematic approach that combines technical assessment, regulatory compliance checks, and risk management protocols. Procurement and IT teams must examine data protection measures, security certifications, incident response capabilities, and contractual safeguards before engaging any AI service provider.
With artificial intelligence transforming business operations, organisations face unprecedented security challenges when selecting AI vendors. The stakes are particularly high given the sensitive data these systems process and the potential impact of security breaches. As outlined in our comprehensive enterprise AI privacy guide, proper vendor evaluation forms the foundation of any secure AI implementation strategy.
What Security Questions Should You Ask AI Vendors?
The right security questionnaire can reveal critical information about an AI vendor’s security posture. Your evaluation should focus on specific technical controls, operational procedures, and governance frameworks that directly impact data protection.
Infrastructure Security Questions: Read more: The Comprehensive Guide to Enterprise AI Privacy & Security Compliance in 2026
- What encryption standards do you use for data in transit and at rest?
- How do you implement network segmentation and access controls?
- What backup and disaster recovery procedures are in place?
- Do you maintain SOC 2 Type II or ISO 27001 certifications?
- How frequently do you conduct penetration testing and vulnerability assessments?
Data Handling and Privacy: Read more: The Comprehensive Guide to Enterprise AI Privacy & Security Compliance in 2026
- How is training data sourced, processed, and stored?
- What data retention and deletion policies apply to customer data?
- Can you guarantee data residency within specific geographic boundaries?
- How do you prevent data leakage between different customer environments?
- What procedures exist for handling data subject requests under UK GDPR?
CallGPT 6X addresses many of these concerns through its innovative local PII filtering technology, which processes sensitive data within the user’s browser before any information reaches AI providers. This architectural approach ensures that National Insurance numbers, payment card details, and other personally identifiable information never leave the user’s environment. Read more: The Comprehensive Guide to Enterprise AI Privacy & Security Compliance in 2026
Essential AI Vendor Security Assessment Criteria
A comprehensive AI vendor security assessment must evaluate multiple dimensions of security maturity. These criteria help distinguish between vendors with robust security programmes and those with superficial compliance measures.
Technical Security Controls
Examine the vendor’s implementation of fundamental security controls. Look for multi-factor authentication, role-based access control, encryption key management, and secure development practices. The vendor should provide detailed documentation about their security architecture, including network diagrams and data flow mappings.
Operational Security Measures
Assess how the vendor manages security operations on a day-to-day basis. This includes incident response procedures, security monitoring capabilities, patch management processes, and staff security training programmes. Request metrics on security incident frequency, response times, and resolution rates.
Third-Party Risk Management
AI vendors often rely on cloud infrastructure providers and other third-party services. Evaluate how they assess and monitor the security posture of their supply chain partners. Request copies of third-party security assessments and understand how contractual security requirements flow down to subprocessors.
CallGPT 6X users report 55% average savings compared to managing separate subscriptions whilst maintaining enterprise-grade security through unified vendor management and consolidated security oversight.
Data Privacy and UK GDPR Compliance Requirements
UK organisations must ensure their AI vendors comply with the Data Protection Act 2018 and UK GDPR requirements. This involves examining both technical capabilities and procedural compliance measures.
Legal Basis and Processing Purposes
Verify that the vendor can clearly articulate the lawful basis for processing personal data and restrict processing to specified purposes. The vendor should provide standard contractual clauses that comply with ICO guidance and establish appropriate data controller/processor relationships.
International Data Transfers
Post-Brexit, UK organisations face complex requirements when transferring data to AI vendors outside the UK. Assess whether vendors have implemented adequacy decisions, standard contractual clauses, or other approved transfer mechanisms. Pay particular attention to US-based vendors and their compliance with relevant data transfer frameworks.
Data Subject Rights
Evaluate the vendor’s ability to support data subject rights, including access, rectification, erasure, and portability. Request documentation of their procedures for handling data subject requests and typical response timeframes. The vendor should also demonstrate technical capabilities for data identification and extraction.
| Compliance Area | Key Requirements | Assessment Questions |
|---|---|---|
| Data Processing Agreements | Article 28 compliance, UK addendums | Are standard DPAs available? Do they include UK-specific provisions? |
| Transfer Mechanisms | Adequacy decisions, SCCs | What mechanisms govern international transfers? Are they ICO-approved? |
| Technical Measures | Pseudonymisation, encryption | What technical safeguards protect personal data? Can you demonstrate effectiveness? |
| Breach Notification | 72-hour reporting, customer notification | What are your breach notification procedures? How quickly do you notify customers? |
Evaluating AI Vendor Risk Management Frameworks
Strong AI vendor security extends beyond technical controls to encompass comprehensive risk management frameworks. These frameworks should address both traditional cybersecurity risks and AI-specific challenges such as model poisoning, adversarial attacks, and bias amplification.
Risk Assessment Methodologies
Request documentation of the vendor’s risk assessment processes, including how they identify, analyse, and prioritise security risks. Look for evidence of regular risk reviews, stakeholder involvement, and integration with business decision-making processes. The methodology should specifically address AI-related risks such as training data contamination and model inference attacks.
Continuous Monitoring and Threat Intelligence
Effective AI vendors maintain robust monitoring capabilities that can detect both traditional cyber threats and AI-specific attack patterns. Evaluate their security information and event management (SIEM) capabilities, threat intelligence sources, and incident correlation processes. Ask for examples of how they’ve detected and responded to AI-targeted attacks.
Business Continuity and Resilience
Assess the vendor’s business continuity planning and disaster recovery capabilities. AI services often require significant computational resources and specialised infrastructure, making resilience planning more complex than traditional software services. Review their recovery time objectives, backup procedures, and alternative processing capabilities.
Security Certifications and Standards for AI Vendors
Security certifications provide valuable third-party validation of an AI vendor’s security controls, but they must be evaluated carefully to ensure they’re current, relevant, and comprehensive.
Core Security Certifications
ISO 27001 certification demonstrates a systematic approach to information security management, whilst SOC 2 Type II reports provide detailed testing of security controls over a specified period. Cyber Essentials certification shows compliance with UK government cybersecurity standards, particularly important for public sector procurement.
Cloud and Infrastructure Certifications
Many AI vendors rely on cloud infrastructure providers for their underlying computing resources. Verify that these providers maintain appropriate certifications such as CSA STAR, FedRAMP (for US-based services), or G-Cloud framework approval for UK government use.
AI-Specific Standards
Emerging standards like IEEE 2857 (Privacy Engineering) and ISO/IEC 23053 (Framework for AI systems using ML) provide frameworks specifically designed for AI system security. Whilst adoption remains limited, forward-thinking vendors may demonstrate compliance with these evolving standards.
The National Cyber Security Centre provides comprehensive guidance on evaluating cloud service security, much of which applies to AI vendor assessment.
Due Diligence Process for AI Vendor Selection
Structured due diligence processes help procurement and IT teams systematically evaluate AI vendor security whilst ensuring consistent assessment criteria across different vendors and use cases.
Pre-Qualification Screening
Establish minimum security requirements that vendors must meet before detailed evaluation. This typically includes current security certifications, insurance coverage, and basic compliance attestations. Pre-qualification screening helps focus detailed assessment efforts on viable candidates.
Technical Security Review
Conduct in-depth technical reviews with qualified security professionals. This may include architecture reviews, code assessments, penetration testing results analysis, and configuration audits. Consider engaging third-party security specialists if internal expertise is limited.
Reference Checking and Site Visits
Speak with existing customers about their security experiences with the vendor. Ask specifically about security incidents, support responsiveness, and compliance assistance. For high-risk implementations, consider conducting site visits to observe security controls firsthand.
Contract Negotiation and Security Clauses
Ensure contracts include comprehensive security clauses covering data protection requirements, incident notification procedures, audit rights, and liability provisions. Security requirements should be specific and measurable rather than generic commitments to “industry best practices.”
Post-Procurement Security Monitoring and Reviews
AI vendor security assessment doesn’t end with contract signature. Ongoing monitoring and periodic reviews help ensure continued compliance with security requirements and identify emerging risks.
Continuous Security Monitoring
Establish regular reporting requirements for security metrics, incident notifications, and compliance status updates. Many organisations require quarterly security reports and annual compliance attestations from their AI vendors.
Periodic Security Reviews
Conduct comprehensive security reviews annually or following significant changes to the vendor’s services or your risk profile. These reviews should reassess the original security criteria and evaluate any new risks that have emerged.
Incident Response Coordination
Develop clear procedures for coordinating security incident response with your AI vendors. This includes notification requirements, escalation procedures, and evidence preservation protocols. Regular incident response exercises help ensure these procedures work effectively under pressure.
CallGPT 6X’s unified platform approach simplifies post-procurement security monitoring by providing centralised oversight of multiple AI providers through a single interface, reducing the complexity of managing multiple vendor relationships whilst maintaining comprehensive security visibility.
Frequently Asked Questions
What security questions should you ask AI vendors?
Focus on infrastructure security, data handling procedures, compliance certifications, and incident response capabilities. Essential questions include encryption standards, data retention policies, geographic data residency options, and procedures for handling data subject requests under UK GDPR.
How do you evaluate AI vendor data privacy compliance?
Review data processing agreements, assess international transfer mechanisms, verify technical privacy safeguards, and examine procedures for supporting data subject rights. Ensure vendors can demonstrate compliance with Data Protection Act 2018 and UK GDPR requirements.
What are the key security risks when procuring AI services?
Primary risks include unauthorised data access, inadequate encryption, insufficient access controls, data residency violations, third-party security weaknesses, and lack of incident response capabilities. AI-specific risks include model poisoning, adversarial attacks, and training data contamination.
How do you assess AI vendor compliance with regulations?
Examine current compliance certifications, review audit reports, assess contractual compliance commitments, and verify technical implementation of regulatory requirements. Request evidence of regular compliance monitoring and reporting procedures.
What security certifications should AI vendors have?
Look for ISO 27001, SOC 2 Type II, and Cyber Essentials certifications as foundational requirements. Additional certifications may include CSA STAR for cloud services, industry-specific standards, and emerging AI security frameworks where available.
Selecting secure AI vendors requires careful evaluation of technical controls, compliance capabilities, and risk management frameworks. CallGPT 6X’s innovative local PII filtering and unified platform approach addresses many common security concerns whilst providing the flexibility and cost savings of multi-provider access.
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