# Which Company Data Should Never Be Sent to Cloud AI Services: A Practical Guide

> Learn how to distinguish data safe for cloud AI from confidential information that must stay inside your company. Clear criteria, examples, and risk-assessment steps — no legal jargon.

- Author: Yaroslav Maxymovych (Founder & CEO, AI Advisory Board)
- Published: 2026-09-10
- Updated: 2026-10-25
- Source: https://aiadvisoryboard.me/blog/which-company-data-should-never-be-sent-to

First paragraph — a short 2–3 sentence introduction that names the reader's pain in their own words. No "hello" and no repetition of the headline.

The founder expects AI to cut routine work but fears that after the first request to a cloud service, a data leak will destroy reputation or trigger fines. The question isn't whether AI is useful, but which specific data cannot be entrusted to it — and which can.

## TL;DR
- Do NOT send to cloud AI any data that could restore a client's or employee's identity: full name, address, phone, ID numbers, bank details.
- Do NOT send commercial secrets with direct monetization value: pricing models, supplier negotiations, draft contracts, margin calculations.
- For aggregated data (summarized metrics, anonymous templates, public company details) risk is minimal — they can be sent to AI after internal review.

## What Exactly Constitutes Confidential Data in the AI Context

The core risk isn't the act of sending text to the cloud, but the possibility of restoring personally or commercially significant details from the AI's response or service logs. If, after processing a query, the cloud AI allows restoration of a client's passport number, purchase history, or internal supplier price — this is no longer "animated text"; it's a leak.

Thus, the criterion is simple: can the received result or intermediate log allow restoration of the source data? If yes — do not send the data.

Example: you ask AI: "Create a commercial proposal for client ООО «Соняшник» for 500,000 UAH with a 10% discount." If your request includes the client's name, amount, and discount — that's already PII + financial data. If the service trains on such requests or stores logs — the risk of restoring the real agreement emerges.

## Which Specific Data Types Should Not Be Sent

### Personal Data of Clients and Employees
This includes:
- Full name, date of birth, place of residence.
- Passport numbers, tax IDs, driver's license numbers.
- Phone numbers, email addresses tied to individuals.
- Bank details, transaction history, scanned receipts.

This is data through which a person can be directly identified. Even if you send only a fragment (e.g., three digits from a passport), AI could combine it with other sources and restore the full number.

### Commercial Secrets with Monetization Value
This is data the company actively protects because it impacts profit:
- Cost tables and margin calculation formulas.
- Draft commercial proposals not yet sent to clients.
- Terms and prices from ongoing supplier negotiations (especially if they differ from public ones).
- Client lists with purchase history and sectors (e.g., "top-10 buyers last quarter").
- Internal demand forecasts, production plans, delivery schedules.

If the data allows a competitor to reverse-engineer your pricing model or understand how you negotiate — it's a commercial secret, not just "internal information."

### Technical Infrastructure Details
Also risky are:
- Network diagrams, server IP addresses, logins to internal systems (even in test format).
- Database structures, table names containing PII or finances.
- Automation scripts with hardcoded access parameters.

Such data doesn't directly lead to PII leaks but could simplify an attack on your systems if it falls into the wrong hands.

## Which Data Can Be Sent (With Verification)

Not everything outside the public domain is forbidden. The following data types are usually safe if you perform two actions before sending:

1. Aggregate the data (sum, average, remove identifiers).
2. Verify that the result does not allow source restoration.

Examples of safe data:
- Total monthly sales without client breakdown.
- Average order value by product category (without specific store or client name).
- Number of received complaints by issue type (without order numbers or PII).
- A letter template with fillable fields where data comes from a local database (e.g., order confirmation template where AI only formulates text, and data is inserted by your system).

In this format, AI receives only structure and logic, while confidential data remains inside your perimeter.

## Practical Checklist for Evaluating a Request Before Sending

Before sending any text to cloud AI, ask yourself four questions:

1. Does the request contain client or employee PII (name, surname, address, phone, email)?
2. Does the request contain data through which profit or loss of a specific deal can be calculated (prices, discounts, cost, margin)?
3. Does the request contain internal infrastructure details (logins, network diagrams, database names)?
4. Can the source of at least one of the above elements be restored from the result or logs?

If the answer to any question is "yes" — do not send the data to the cloud service without prior anonymization or use of local AI.

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## Definition

> **Definition:** Personal data — any information by which a person can be directly or indirectly identified (full name, tax ID, passport number, address, phone).

> **Definition:** Commercial secret — information that has economic value because it is not known to others and is subject to reasonable protective measures (pricing forms, supplier negotiations, cost).

> **Definition:** Anonymization — the process of removing or replacing data identifiers so that restoring a person or source becomes impossible (replacing PII with ID, summing finances, aggregating by period).

## FAQ

**Can data be sent to cloud AI if it's encrypted?**
No, if you send an encrypted array — it's safe for transit, but if decryption happens on the service side (i.e., AI sees the plaintext), the risk remains. Encryption protects data in motion, not from processing.

**Is an NDA with the AI provider needed for data protection?**
NDA is a legal tool, but it doesn't prevent technical data leaks via logs or model training. Start with technical separation: what exactly to send, and what not to.

**How to verify if data is sufficiently anonymized?**
Try to restore the source from the result. If you can determine which client, deal, or internal parameter stands behind the request — anonymization is insufficient. Repeat aggregation or add noise.

## Conclusion

Not all data is equally unsafe for cloud AI. Client personal data and commercial secrets with monetization value — this is what must stay inside the company or be sent only after strict anonymization. Tomorrow, take the first step: take one request your team regularly sends to AI and apply the checklist above — you'll immediately see whether a change is needed.
If you'd like to discuss your situation — a free 30-minute consultation-diagnostic is available on request.

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