AI Vendor Security Review: What to Ask

When evaluating AI sales tools, security cannot be an afterthought. The primary questions for an AI vendor security review revolve around data handling, compliance, infrastructure security, access controls, and incident response. These inquiries ensure your sensitive sales data remains protected and your operations stay compliant.

Sales teams are increasingly adopting AI, which means sharing more data with third-party vendors. This data can include customer contact information, sales conversations, pipeline details, and proprietary strategies. Without a rigorous security review, you expose your organization to significant risks, including data breaches, compliance violations, and reputational damage.

This guide outlines the critical questions to ask during an AI vendor security review. It helps you assess potential risks and make informed decisions, ensuring your AI adoption is secure and responsible.

Data Handling and Privacy Questions

Data is the lifeblood of sales AI. Understanding how a vendor handles your data is paramount.

What data does the AI tool collect, store, and process?

Be specific. Does it ingest CRM data, email content, call recordings, calendar entries, or other sensitive information? Understand the scope of data access.

Where is the data stored (geographic location) and what are the data residency policies?

Data sovereignty laws vary by region. Ensure the vendor’s storage locations align with your regulatory obligations and internal policies. Some industries or countries have strict requirements about where data must reside.

How is data encrypted, both in transit and at rest?

Encryption is a fundamental security measure.

• In transit: Data should be encrypted using protocols like TLS 1.2 or higher.
• At rest: Data stored on servers or databases should be encrypted using industry-standard algorithms (e.g., AES-256).

What are the vendor’s data retention and deletion policies?

Understand how long the vendor keeps your data and their process for secure deletion once you terminate the service. Can you request immediate deletion of specific data?

How does the vendor ensure data privacy and compliance with regulations (e.g., GDPR, CCPA, HIPAA)?

Request documentation of their compliance efforts. This might include privacy impact assessments, data processing agreements (DPAs), and details on how they handle data subject rights requests (e.g., right to access, right to be forgotten).

Is data anonymized or pseudonymized for AI model training or analytics?

If the vendor uses your data to improve their models or for aggregated analytics, confirm that personal identifiers are removed or masked. This reduces the risk of re-identification.

Compliance and Certifications

A vendor’s certifications provide an independent validation of their security posture.

What security certifications and attestations does the vendor hold (e.g., SOC 2 Type 2, ISO 27001, HIPAA)?

Request copies of their most recent audit reports.

“A vendor’s certifications provide an independent validation of their security posture.”

Can the vendor provide a copy of their security policy and data protection addendum (DPA)?

Review these documents thoroughly. The security policy outlines their internal controls, while the DPA details their obligations regarding your data under privacy regulations.

How does the vendor handle third-party sub-processors?

AI tools often rely on other services (e.g., cloud providers, analytics tools). Understand how the vendor vets and monitors the security practices of their sub-processors.

Infrastructure and Network Security

The underlying infrastructure where the AI tool operates must be secure.

What cloud provider does the vendor use (e.g., AWS, Azure, GCP) and what security measures are in place at the infrastructure level?

While cloud providers offer robust security, the vendor is responsible for configuring and managing their instances securely. Inquire about their use of security groups, network segmentation, and vulnerability scanning.

How does the vendor protect against common web application vulnerabilities (e.g., OWASP Top 10)?

Ask about their secure coding practices, regular security testing (penetration testing, static/dynamic application security testing), and use of web application firewalls (WAFs).

What measures are in place for disaster recovery and business continuity?

Understand how the vendor ensures service availability and data recovery in case of an outage or disaster. This includes backup strategies, recovery time objectives (RTOs), and recovery point objectives (RPOs).

Does the vendor conduct regular vulnerability scanning and penetration testing? Can you provide reports?

Regular testing helps identify and remediate weaknesses. Request executive summaries of recent penetration test reports, focusing on the scope and findings.

Access Control and Authentication

Controlling who can access your data, both internally at the vendor and externally, is critical.

What authentication methods are supported (e.g., SSO, MFA)?

Strong authentication is non-negotiable. Single Sign-On (SSO) with your identity provider (e.g., Okta, Azure AD) and Multi-Factor Authentication (MFA) should be standard.

How does the vendor manage internal access to customer data?

Inquire about their least privilege access policies, role-based access controls, and background checks for employees with access to sensitive systems.

Is there an audit trail for data access and changes within the AI platform?

Detailed logs of who accessed what data, when, and what actions were taken are essential for accountability and forensic analysis.

How does the vendor handle offboarding of employees with access to customer data?

Ensure there is a robust process for revoking access immediately upon an employee’s departure.

Incident Response and Monitoring

Even with the best preventative measures, incidents can occur. A strong incident response plan is crucial.

What is the vendor’s security incident response plan?

Request a summary of their plan, including detection, containment, eradication, recovery, and post-incident analysis.

How quickly will the vendor notify us in the event of a data breach or security incident affecting our data?

Look for clear service level agreements (SLAs) for notification, ideally within 24-72 hours, depending on the severity and regulatory requirements.

What monitoring and logging capabilities does the vendor have in place to detect suspicious activity?

Understand their use of Security Information and Event Management (SIEM) systems, intrusion detection/prevention systems (IDS/IPS), and continuous monitoring tools.

How does the vendor conduct forensic analysis after an incident?

Inquire about their capabilities to investigate the root cause, scope, and impact of a security incident.

AI-Specific Security Considerations

AI introduces unique security challenges beyond traditional software.

How does the vendor protect against model inversion attacks or data leakage from the AI model itself?

Model inversion attacks can potentially reconstruct sensitive training data from the model’s outputs. Ask about techniques like differential privacy or secure multi-party computation if relevant.

What measures are in place to prevent adversarial attacks on the AI model (e.g., data poisoning, model evasion)?

Adversarial attacks can manipulate AI models to produce incorrect or malicious outputs. Inquire about their robustness testing and defense mechanisms.

How does the vendor ensure the integrity and provenance of the data used for AI model training?

Data poisoning can compromise model integrity. Ask about data validation, source verification, and anomaly detection in training data pipelines.

Are there controls to prevent unauthorized access or manipulation of the AI model’s parameters or weights?

The core of the AI model needs protection from tampering.

Vendor Relationship and Ongoing Security

Security is not a one-time check; it is an ongoing process.

How often does the vendor review and update their security practices?

Security is dynamic. The vendor should have a continuous improvement process for their security posture.

What is the process for reporting security vulnerabilities to the vendor?

Ensure they have a clear, publicized vulnerability disclosure program.

Will the vendor participate in security questionnaires or audits required by our organization?

Many organizations have their own security assessment processes. Confirm the vendor’s willingness to cooperate.

What is the vendor’s policy on security updates and patches for their software?

Timely patching of vulnerabilities is crucial. Understand their patch management process and communication strategy.

Next Steps After the Review

Once you have gathered answers to these questions, consolidate the information. Involve your internal IT security and legal teams in reviewing the vendor’s responses and documentation. They can provide expert analysis and identify any red flags.

Compare the vendor’s security posture against your organization’s internal security policies and regulatory requirements. Identify any gaps or areas of concern. If there are significant issues, either negotiate with the vendor for remediation or consider alternative solutions.

“A thorough security review is a critical component of any AI vendor evaluation.”

It protects your data, maintains compliance, and builds trust in your AI initiatives. For a broader perspective on evaluating AI tools, refer to our guide on AI vendor evaluation and our RFP checklist for AI sales vendors. These resources can help you integrate security considerations into your overall vendor selection process.