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AI Governance & Security

How to Answer Enterprise Security Questionnaires for AI Products

Shoppeal Tech·AI Engineering & Strategy Team10 min readLast updated: March 4, 2026

Quick Answer

Shoppeal Tech has completed 40+ enterprise security questionnaires for AI products across BFSI, healthtech, and enterprise SaaS. The AI-specific section covering model governance, training data provenance, hallucination controls, and prompt injection defences kills 60% of deals for unprepared teams. BoundrixAI's pre-built compliance documentation reduces questionnaire completion time from 3 weeks to 48 hours.

150 Qs

Avg Questionnaire Length

30–50

AI-specific Questions

60%

Deal Kill Rate

48 hrs

Shoppeal Completion Time

The 8 AI-Specific Question Categories That Kill Deals

1. Model provenance: Which foundation models do you use? Are they open-source or proprietary? What are the training data licences?

2. Data handling: Does customer data get sent to third-party AI APIs? Is it used for model training? How long is it retained?

3. Hallucination controls: How do you detect and prevent hallucinated outputs? What is your false-positive/false-negative rate?

4. Prompt injection defence: What controls prevent adversarial prompt injection? How do you separate system prompts from user inputs?

5. Audit logging: Do you log every AI inference request and response? How long are logs retained? Are they tamper-proof?

6. Access controls: Who in your organisation can access customer data used for AI? Do you enforce least-privilege?

7. Model updates: How are you notified when underlying models change? How do you validate that updates don't degrade performance?

8. Subprocessors: Which third-party AI APIs, vector databases, and cloud providers process customer data?

Model-by-Model Answer Templates

If you use OpenAI API: 'Customer data is transmitted to OpenAI for inference only. OpenAI's Enterprise API does not use customer data for model training under their data processing addendum (DPA). Data is retained for 30 days for abuse monitoring only. We have a signed DPA with OpenAI.'

If you use open-source models (Llama, Mistral): 'We run inference on our own GPU infrastructure. No customer data leaves our VPC. Model weights are stored on isolated compute with no internet egress.'

For hallucination controls: 'All AI outputs pass through a validation layer that: (1) checks citations against source documents, (2) applies confidence scoring, (3) flags low-confidence responses for human review. Outputs below [threshold] are blocked automatically.'

Building a Reusable Security Pack

The investment with the highest ROI in enterprise AI sales is building a security pack once and reusing it for every deal.

Your security pack should include: SOC2 Type II report or in-progress attestation letter; penetration test report (< 12 months old); data processing addendums with all subprocessors; DPDP/GDPR compliance attestation; AI-specific risk assessment; BCP/DR documentation; model governance policy.

Shoppeal Tech builds this security pack for clients in 4-6 weeks. Once built, questionnaire completion drops from 3 weeks to 48 hours for every subsequent deal.

Frequently Asked Questions

What is the most common reason AI products fail enterprise security reviews?
The most common failure is sending customer data to third-party AI APIs without a signed Data Processing Agreement (DPA), without disclosure in the security questionnaire, and without customer consent in the service agreement. This is both a security failure and a contractual breach.
Do we need SOC2 to pass enterprise security questionnaires?
SOC2 Type II is strongly preferred for enterprise deals above $50K ACV. Below that, a credible 'SOC2 in progress' attestation + clear security controls documentation often satisfies procurement teams, especially in India where SOC2 penetration is growing but not yet universal.
enterprise security questionnaireAI complianceSOC2procurementAI security

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