# ERP AI Vendor Due Diligence: What CIOs Should Actually Check

> Source: https://netray.co/erp-help/cio-erp-ai-vendor-due-diligence
> Publisher: Netray (netray.co), AI and integration engineering for ERP and manufacturing systems.
> Section: ERP Help

## Short answer

The single highest-signal question in ERP AI vendor due diligence is 'show me it answering a real question against our actual ERP data, live, not a demo dataset.' Beyond that, focus diligence on data grounding method, security and access model, exit/portability terms, and references from customers on your specific ERP platform - not on feature checklists, which most vendors can match on paper.

## Kind

cio

## System

cio

## Erp

ERP Strategy (any platform)

## Module

Vendor Evaluation / Procurement

## Query

What due diligence should we do before choosing an ERP AI vendor

## Alternate Queries

- ERP AI vendor evaluation checklist
- how to vet an ERP AI copilot vendor
- questions to ask ERP AI vendors
- ERP AI vendor selection due diligence

## Applies To

Any organization evaluating an ERP AI copilot, chatbot or agent vendor, on any ERP platform

## Steps

### Due diligence checklist before signing

**Items:**

Require a live demo against a sample of your actual ERP data or a close structural equivalent - reject demos run only on the vendor's polished sample dataset.

Ask exactly how the tool is grounded: does it query the ERP live, does it use a periodically refreshed index, or does it rely on the underlying model's general training data (the weakest and riskiest option for ERP-specific answers).

Get the access and security model in writing: what ERP credentials or API scopes the tool needs, whether it can write back to the ERP, and how access is revoked.

Request three references from customers on your specific ERP platform and company size, not generic testimonials - platform-specific quirks are where most implementations succeed or fail.

Ask what happens to your configuration, prompts, and any fine-tuning or custom grounding work if you leave the vendor - is it portable, or is it a total rebuild with a new vendor.

Check whether the vendor's AI features depend on a third-party model provider, and what happens contractually and technically if that provider changes pricing or availability.

Pilot before committing to a multi-year contract - a vendor unwilling to run a scoped, time-boxed pilot before a long-term commitment is a warning sign, not a scaling decision.

## Sections

### The demo test that filters out most vendors immediately

**Body:**

A surprising number of ERP AI products in 2026 are a general-purpose chatbot wrapper with an ERP logo and a curated demo dataset, with little real integration to a live ERP instance. The fastest filter is asking to see the tool answer a specific, slightly awkward question against your own data during the evaluation - not the vendor's rehearsed demo flow. Something like 'what is the current on-hand quantity for item X at our second warehouse' exposes within minutes whether the tool is actually grounded in live ERP data or just producing plausible-sounding text.

Vendors with a genuinely grounded product welcome this test because it is where they differentiate. Vendors who redirect to a scripted demo, insist on more prep time than the question warrants, or provide an answer that cannot be traced back to a specific ERP record or query, have failed the single most important diligence check.

### Grounding method: the technical question that predicts everything else

**Body:**

Ask precisely how the tool gets its ERP knowledge. Live query grounding (the tool runs a real query, saved search, or API call against the ERP at the moment of the question) gives current, traceable answers but requires more integration work upfront. Periodic index grounding (the tool searches a refreshed copy or embedding of ERP data) is faster to deploy but can serve stale answers if the refresh interval is long, which matters a lot for inventory or order-status questions and less for policy or documentation questions.

The weakest and most common failure mode is a tool relying mainly on the underlying language model's general training knowledge, occasionally supplemented with ERP context, rather than being grounded in your specific instance's data at all. This produces fluent, confident, and sometimes entirely wrong answers about your specific configuration, data or history - exactly the failure mode that destroys user trust fastest.

### Lock-in and portability

**Body:**

Before signing, get a clear answer on what happens to the work product - saved grounding configurations, custom prompts, fine-tuned behavior, integration mappings - if the relationship ends. Some vendors, particularly ERP-native copilots bundled into a cloud subscription, tie the AI layer so tightly to their specific platform version that switching means starting over entirely, which is a legitimate business choice but should be priced into the decision, not discovered during a later renewal negotiation.

Ask specifically: can we export our grounding configuration or prompt library, and would a competing vendor or an in-house team be able to use it as a starting point. A vendor with confident, specific answers to this question is generally more trustworthy on other fronts too.

### References that actually predict success

**Body:**

Generic customer logos and testimonials tell you almost nothing about ERP AI vendor fit, because the hard part of these projects is almost always platform-specific: how well the vendor's product handles your ERP's particular data model, customizations, and API quirks. A reference from a customer on the same ERP platform, at a similar company size and industry, who is 6+ months past go-live, is worth far more diligence weight than five logos on a website. Ask that reference specifically what broke during rollout and how the vendor responded - the answer to that question is more informative than anything in the sales deck.

## Pitfalls

- Evaluating only on a curated vendor demo dataset instead of insisting on a live test against real or structurally similar ERP data.
- Not asking how the tool is grounded, and discovering post-purchase that it relies mostly on general model knowledge rather than your ERP's actual data.
- Signing a multi-year contract without a time-boxed pilot, based on a sales presentation alone.
- Skipping the portability question and discovering full vendor lock-in only at renewal time, with no leverage to negotiate.
- Accepting generic reference customers instead of insisting on references from the same ERP platform and similar company size.
- Ignoring what third-party model provider the vendor depends on, and being surprised later by a pricing or availability change outside the vendor's control.

## Ai Angle

Netray's ERPray and SyteRay deployments are grounded in live queries and saved searches against a customer's actual ERP instance, and prospective customers are routinely invited to bring a real, slightly awkward question to a live evaluation rather than watching a scripted demo. Grounding configurations and integration mappings built during an engagement are documented and remain usable by the customer, addressing the portability question directly rather than leaving it for a renewal negotiation.

## Faq

### What is the single best question to ask an ERP AI vendor during evaluation?

**Answer:** Ask them to answer a specific, unscripted question against your real ERP data live during the meeting. How they respond to that request reveals more about the product than any feature list or case study.

### How do we know if a vendor's tool is actually grounded in our ERP versus relying on general AI knowledge?

**Answer:** Ask them to explain the grounding mechanism precisely - live query, refreshed index, or general model knowledge - and then test it with a question whose answer only exists in your specific ERP instance, such as a recent transaction or a custom field value.

### Should we always run a pilot before signing a full contract?

**Answer:** Yes. A scoped, time-boxed pilot (typically 4-8 weeks) against one real use case is standard practice and a reasonable request of any serious vendor. Reluctance to pilot before a multi-year commitment is a significant warning sign.

### How important are vendor references really?

**Answer:** Very, but only if platform-specific. A reference from a customer on your exact ERP platform and similar company size, at least six months past go-live, is far more predictive than generic testimonials or unrelated case studies.

### What does vendor lock-in look like specifically for ERP AI tools?

**Answer:** It typically shows up as non-portable grounding configurations, prompts or fine-tuned behavior that cannot be exported or reused with another vendor, forcing a full rebuild if you switch. Ask about this explicitly before signing, not at renewal.

## Search terms

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