AI vendor questionnaire: Essential questions to ask

Adopting third-party AI tools can accelerate your business goals, but it also introduces complex risks that aren’t always obvious from a sales demo. How can you be sure a vendor’s claims about security, fairness, and compliance hold up under scrutiny? You need a structured, repeatable process as part of your AI procurement policy to look past the flashy marketing and assess the technology for what it truly is.

This is where a well-designed AI vendor questionnaire becomes your most critical due diligence tool. It formalizes your evaluation, forcing potential partners to provide clear, written answers about their data handling, model governance, and security protocols, allowing you to make an evidence-based decision with confidence.

What is an AI vendor questionnaire?

Your AI vendor questionnaire is a structured set of questions you send to potential AI providers before you even think about signing a contract. A well-designed questionnaire allows your business to systematically assess potential AI partners, confirming their technology is not only powerful but also aligns with your company’s risk tolerance, ethical principles, and compliance obligations.

By asking targeted questions about data handling, model fairness, security protocols, and regulatory adherence, you create a standardized process for comparison. This helps you move from a subjective feeling to an objective, evidence-based decision.

What to ask: Core components of your questionnaire

A strong AI vendor questionnaire relies on a few core pillars. Think of these as the non-negotiable categories you need to explore to get a complete picture of a potential partner. By structuring your inquiry around the following four areas, you can create a standardized process to effectively compare vendors and protect your organization from unforeseen liabilities.

Data privacy, security, and transparency

Partnering with a third-party AI provider often means entrusting them with your data. Your priority is to confirm they will handle it responsibly. A vendor’s policies on data privacy and security should be clear, comprehensive, and readily available.

You need to understand their protocols for data encryption, both in transit and at rest, where they will store your data, and who has access to it. You should also ask whether the vendor uses your data to improve its AI, as this can lead to “leakage,” in which your company’s information is learned and shared with other users by the vendor’s AI. Request their data retention and deletion policies to ensure they align with your internal governance and any relevant data protection laws.

Model performance and explainability

AI vendors must be able to explain how the models that underpin their technology work and how they perform. This includes the data the model was trained on, its source, whether it’s copyrighted, and its bias assessment. You’ll want to know about performance, reliability, and bias monitoring, as well as the results of any audits in these areas.

Compliance, governance, and ethics

In a rapidly evolving regulatory landscape, your vendor’s compliance approach is paramount. A responsible partner must demonstrate a straightforward process for staying current with emerging AI regulations and ensuring their solutions adhere to them. Ask how they manage ethical considerations and what frameworks they have in place to address potential AI bias. For instance:

• Have they adopted an AI management framework, such as ISO 42001 or NIST AI RMF?
• Do they have an internal ethics board?
• How do they document model testing and validation for auditing purposes?

Their answers will reveal their commitment to responsible AI and their ability to help you meet your own compliance obligations, which is especially important for organizations in highly regulated industries.

Support, implementation, and scalability

An excellent AI tool is only effective if your team can use it properly, and it can grow with your business. Your questionnaire should focus on the practical aspects of the partnership. Ask about their standard implementation process, what kind of training they provide for your team, and what their customer support model looks like. Evaluate the quality of the instructions they provide — do they clearly describe how the model should (and shouldn’t) be used?

It’s also essential to understand how the solution scales. Will performance suffer as your usage increases? What are the associated cost structures for growth? The vendor’s answers will give you a clear idea of the total cost of ownership and how well they will function as a long-term, strategic technology partner.

How to design an effective questionnaire

Creating a questionnaire that gets you the answers you need is both an art and a science. It’s not just about listing questions; it’s about structuring a conversation that reveals a potential partner’s true capabilities and values. A well-crafted questionnaire becomes a strategic asset, helping you move from a long list of possible vendors to a shortlist of true partners.

Download our checklist

A well-crafted AI vendor questionnaire is a strategic safeguard that enables you to vet third-party AI providers in a comprehensive, consistent manner. This not only protects your organization from hidden risks but also strengthens your ability to adopt AI responsibly and at scale. As part of a broader AI procurement policy, your questionnaire becomes one of your most powerful tools for measuring and mitigating AI risk, turning due diligence into a competitive advantage.

To help you get started, we’ve developed a checklist of 10 essential questions for your AI vendors. Download it here to begin your journey to responsible AI adoption.

About the authors

Guru Sethupathy is the VP of AI Governance at Optro. Previously, he was the founder and CEO of FairNow (now part of Optro), a governance platform that simplifies AI governance through automation and intelligent and precise compliance guidance, helping customers manage risks and build trust and adoption in their AI investments. Prior to founding FairNow, Guru served as an SVP at Capital One, where he led teams in building AI technologies and solutions while managing risk and governance.