Can You Trust AI Answers From Your ERP? Read-Only, Verified and Logged

Asking an ERP a question in plain language – “top 10 overdue customers”, “dispatch this month versus last” – is one of the most useful things AI can do for a factory owner. It is also one of the riskiest. A chatbot that guesses, mixes up periods or plants, or quietly changes data is worse than no chatbot at all, because people act on its answers. This guide explains what makes AI answers from ERP data trustworthy: read-only access, verified query templates, stating the basis of every answer, review and logging – with a worked week of questions.

Why plain-language questions go wrong

• Ambiguity: “sales this month” – invoiced or ordered? With or without GST? Which plant?
• Made-up answers: a language model asked something it cannot find may produce a plausible number rather than say it does not know.
• Wrong joins: a query that counts an invoice twice because it has two lines gives a confident but wrong total.
• Write access: an assistant that can run any command could, by mistake or misuse, change or delete records.

Five rules for trustworthy AI answers

1. Read-only by design. The AI may only read data – only select queries run – so it cannot change or delete anything. Any action, such as an approval, goes through the ERP’s normal approved interfaces and rights.
2. Verified templates first. Common questions are answered by proven query templates written and checked once. Free-form AI is used only when no template fits.
3. Learn from confirmation. When a free-form answer is confirmed correct, it becomes reusable; when it is rejected, it is never used again.
4. State the basis. Every answer says which period, plant and GST basis it uses, and shows the table behind the number.
5. Log everything. Every question, query and answer is recorded, so a surprising figure can be traced.

Worked example: one week of questions

At Tejaxo Manufacturing (sample data), the owner and two managers asked 20 questions in a week:

Route	Questions	Outcome
Verified template	14	Answered, reused
Free-form AI, confirmed	5	Added as template
Free-form AI, rejected	1	Never reused
Data changed by AI	0	Not possible

14 of 20 – 70% – were common questions answered instantly by verified templates. Five needed free-form AI; the managers checked them against the drill-down table and confirmed them, so next week they will be answered by templates too. One answer was rejected – it had used order date instead of invoice date – and will not be reused. No data was changed, because the assistant could only read. Over time the share of template answers rises and the share of new questions falls, which is exactly the direction you want: more answers that are instant and already proven correct.

What a good answer looks like

A useful answer has four parts: the figure, a one-line summary, the basis (period, plant, GST basis) and a drill-down table that lists the records behind it. If the owner asks for the top overdue customers, the answer should show the customers, the amounts, the oldest bill dates and the period used – so the next action, a phone call, can be taken straight from it. Receivables questions only work if receipts are adjusted bill-wise; see receivables ageing.

Where AI helps most in a factory

• Owner questions that cut across modules – cash, dues, dispatches, backlog; see the owner’s daily dashboard.
• Exceptions – which suppliers are late, which machines had the most downtime, which items have not moved.
• Comparisons – this month versus last, this plant versus that one, this customer this year versus last.
• Reading documents – extracting fields from a supplier invoice at the gate; see AI invoice scanning.

Building the template library

The first month is when the template library grows fastest. Collect the questions the owner and managers actually ask – usually twenty or thirty cover most of the week – and make sure each has a tested template with a clear definition: which date, which documents, which plants, with or without tax. Write the definition into the answer itself so nobody has to guess. After that, new templates come from confirmed free-form answers, and the library keeps pace with the questions people actually ask each week.

Rolling it out

1. Start with the owner and two or three managers who ask cross-module questions every day.
2. Ask them to check the drill-down for the first few weeks and mark answers right or wrong.
3. Review rejected answers weekly – most point to a definition that needs to be agreed, not to a fault in the data.
4. Widen access by role once the common questions are covered by templates.

Questions to ask any AI ERP vendor

• Can the AI change or delete data, or is it read-only?
• Are common questions answered by fixed, tested queries or generated afresh every time?
• Does every answer state its period, plant and tax basis?
• Can I see the records behind every number?
• Is every AI question and answer logged, and who can see the log?
• Where does my data go – does it leave our servers?

Data stays where it should

Factory data – customers, rates, costs – is sensitive. Answers should only be visible to authorised users, the same rights that govern screens should govern questions, and document reading such as invoice OCR is best run on the plant’s own server so data does not leave it. See approval workflows and user rights.

How Tejaxo ERP handles it

Ask Tejaxo AI answers questions in English or Hinglish – metric, period, grouping, top-N and comparisons – with an answer, a summary and a drill-down table, and states the period, plant and GST basis with every answer. It runs verified query templates before any free-form AI; confirmed answers are reused and rejected ones never again. It is read-only by design: only select queries run and the AI cannot change or delete data. Answers show the checks run and are labelled as AI-generated and verified. Under Tejaxo’s AI governance, AI and dashboards read data, writes go only through approved interfaces and every AI action is logged. The same questions can be asked on WhatsApp – see ERP with WhatsApp automation and AI ERP vs traditional ERP.

Common mistakes

• Giving the AI write access “to save time”.
• Trusting a number without its basis – period and plant matter.
• No review loop, so the same wrong answer is repeated.
• Messy master data. Duplicate customers and items give wrong totals whether a person or an AI asks.

Next step

Ask your own questions of your own data in a free demo of Tejaxo ERP.

Frequently asked questions