# Questions to Ask AI Vendors in an ERP RFP > Source: https://netray.co/erp-help/rfp-questions-to-ask-ai-vendors-erp-rfp > Publisher: Netray (netray.co), AI and integration engineering for ERP and manufacturing systems. > Section: ERP Help ## Short answer Ask AI vendors how, not whether: how the assistant reaches ERP data, whose permissions it uses, where each model runs, how answers are tested, what it costs at volume and what you can take with you on exit. Below are the questions grouped by topic, with what a good and a worrying answer sounds like. ## Kind cio ## System cio ## Erp ERP selection and AI ## Module Procurement / vendor questions ## Query questions to ask AI vendors in an ERP RFP ## Alternate Queries - AI vendor RFP questions - questions to ask ERP vendors about AI - AI vendor due diligence questions for ERP - what to ask a vendor about their ERP copilot ## Applies To ERP vendor copilots, third-party ERP AI products, and custom AI builds; relevant to any ERP ## Steps ### How to run the vendor question round **Items:** - Send the same written question set to every bidder, grouped under the headings below, and require answers in writing before demos. - Ask for architecture diagrams showing where data, models and logs sit, and compare them to your security policy. - Hold a technical session with your security lead and an ERP power user, not only sales engineers. - Request reference calls with customers who run the product on an ERP similar to yours and ask what they would change. - Run the proof of value on your sanitized data using your test questions and compare against known ERP results. - Record answers in a table so you can score them consistently after the demos. - Follow up unclear answers in writing; a verbal assurance has no contract value. ## Sections ### Data access and grounding **Body:** Ask: How does the assistant read our ERP data, through documented APIs, database views, or a replicated copy? How fresh is the data? Which tables or business objects are in scope for our modules? Can it show the query or source for each answer? A good answer names the interface and the refresh model. A worrying answer is 'it learns from your data' with no mechanism. Ask: Is any of our data used to train or fine-tune a model, ours or yours? Where do embeddings and vector indexes live? Can we delete them? Ask for the answer per component, since a vendor can truthfully say 'no training' while still retaining prompts in a logging system. Ask: What happens when the answer requires joining ERP data with documents such as quality procedures, contracts or drawings? Many products do one well and fake the other. ### Security, roles and write-back **Body:** Ask: Whose credentials does the assistant use when answering? Does it enforce the asking user's ERP roles and data restrictions? A product using one service account should explain in detail how it filters results, and you should test it with a low-privilege user during the proof of value. Ask: What actions can the assistant take, and what approval is required? Can we run it fully read-only? Is every action logged with user, input and outcome? Ask for the audit record format. Ask about prompt injection: what happens if a supplier document or free-text field contains instructions aimed at the model? The /tools/ai-agent-security-review-checklist and /tools/ai-vendor-evaluation-checklist tools provide longer lists; use them to extend this section if your risk profile is high. ### Models, deployment and quality **Body:** Ask: Which models run in the product, who hosts them, and can we choose or replace them? Can it run on our GPUs or in our private cloud? What is the minimum hardware? What happens to quality if we use a smaller open-weight model? Vendors that depend on a single external model API should state the data terms of that provider. Ask: How do you measure accuracy? Do you have a regression test set, and what happens when you change the model or prompts? Ask for failure examples, not only successes. A vendor who cannot name a failure mode has either not tested widely or is not being candid. Ask: What is your support model for wrong answers? Is there a feedback loop that lets our admins review flagged responses? ### Commercial, roadmap and exit **Body:** Ask: What is the pricing unit, and what would our bill be at our expected volume and at three times that? Which AI features are included in the base ERP subscription, which are add-ons, and how have prices changed over the last two renewals? Ask: What can we export if we leave: configuration, prompts, evaluation sets, embeddings, tuned weights? Which parts rely on proprietary components that cannot move? See cio-erp-vendor-copilot-lock-in for how to weigh the answers. Ask: Which of the capabilities you described are generally available today versus roadmap, and will you commit roadmap items contractually with dates and remedies? ## Pitfalls - Asking yes/no questions that every vendor answers yes. - Letting the demo environment stand in for answers about production architecture. - Not testing role enforcement with a low-privilege account. - Skipping the data-use and logging questions because 'no training' was stated once. - Treating roadmap statements as commitments. - Sending questions only to sales rather than involving the vendor's security and engineering staff. ## Ai Angle Use a grounded assistant on your own side of the table: with read-only access to your ERP it can answer 'which tables hold this data and how many records are involved', which helps you check vendor claims about scope and volume. ERPray-style tooling that shows the generated query also gives you a reference for how a transparent answer should look when you grade vendor demos. ## Faq ### What is the single most important question to ask? **Answer:** Whose permissions does the assistant use, and can you prove it with a low-privilege test user. Role enforcement failures are the commonest serious defect in ERP AI and are invisible in a demo run by an administrator. ### How do I check a vendor's accuracy claims? **Answer:** Do not rely on a quoted percentage. Give them 10 to 20 of your own questions with known answers from the ERP, include a few hidden ones, and grade results yourself. Ask how they would measure it in production after go live. ### Should I ask about the underlying model provider? **Answer:** Yes. If the product sends your data to a third-party model API, you need that provider's data retention, location and training terms, and you need to know whether the vendor can swap models without notice. Ask for it in the contract. ### Are these questions only for third-party AI vendors? **Answer:** No. Ask your ERP vendor the same questions about their built-in copilot. Bundled does not mean secure or private by default, and its deployment, pricing and exit terms may be less flexible than a separate layer. ## Search terms questions to ask AI vendors, AI vendor RFP questions, ERP copilot vendor questions, AI vendor due diligence, RFP questions for AI software, ERP AI vendor evaluation, AI security questions for vendors, ask ERP vendor about AI, AI RFP questionnaire, vendor AI data privacy questions --- Talk to an engineer: https://netray.co/contact?intent=erp_ai | Machine catalog: https://netray.co/agent/catalog.json