AI guide: Which data can you enter without hesitation - and which not?

Artificial intelligence is a tool. It processes input, stores data depending on the provider and can analyse content. Anyone using it should know which information is not critical - and which is not.

1. harmless entries

These types of content are generally low-risk:

General knowledge questions

• „How does photosynthesis work?“
• „Explain to me the difference between a GmbH and an AG.“

Technical or factual problems without real data

• Code examples without real access data
• Mathematical tasks
• General marketing ideas

Anonymised scenarios

• A medium-sized company with 20 employees has the following problem ...“
• „A person feels overloaded at work ...“

Texts without personal details

• Blog designs
• Product descriptions
• Structures
• Style corrections

Principle:
Anything that could be published on the Internet without hesitation is generally uncritical.

2. data that should not be entered

This is where the real risk begins.

Personal data

• Full name + address
• Dates of birth
• Telephone numbers
• E-mail addresses
• Customer data
• Application documents

Access data

• Passwords
• API keys
• Access codes
• TANs
• Credit card numbers

Internal company information

• Unpublished strategies
• Financial data
• Sales figures
• Contract contents
• Source code with security logic

Health data

• Diagnoses
• Therapy reports
• Psychological details with identifiability

Particularly sensitive data according to GDPR

• Religious affiliation
• Political conviction
• Trade union membership
• Biometric data

This data does not belong in an AI system unless there is a clear legal basis and a data protection-compliant environment (e.g. enterprise solutions with an AV contract)

3. why caution is necessary

1. storage and training
Depending on the provider, entries can be used to improve the system (unless deactivated). Even if data is anonymised, a residual risk remains.

2. data leaks
No online system is completely secure. Security incidents occur on a regular basis.

3. misinterpretations
AI can misunderstand content or summarise it incorrectly. With sensitive data, this can have real consequences.

4. breach of confidentiality
Anyone who enters customer data or internal information may be in breach:

• Labour contract
• NDA
• Data protection law
• Professional confidentiality

4. practical safety rules

1. Never enter real personal data.
2. Always abstract or anonymise scenarios.
3. Never copy access data.
4. For corporate use: Involve IT and data protection officers.
5. Check whether an Enterprise tariff with deactivated training is being used.

A simple test helps:
Would I write this information in a public forum?
If not, it does not belong in a freely accessible AI.

5. typical misconceptions

„Nobody reads that.“
Yes - systems can be randomly tested for quality assurance (depending on the provider).

„I only gave one example.“
If real persons are identifiable, it remains personalised.

„It's just a small section.“
Partial information can also be combined.

AI is efficient, but not a confidential space.
General, abstract or creative content is unproblematic.
Personal, confidential or security-relevant data is problematic.

Anyone using AI professionally needs clear internal rules.