Artificial Intelligence (AI) tools are becoming part of everyday business operations. From writing emails and reports to supporting software development, data analysis, and customer service, AI can significantly increase employee productivity.
However, careless use can put confidential data, information security, and even the company’s reputation at risk. This article aims to help employees understand how to use AI tools in a safe, responsible, and cybersecurity-aligned way.
1. AI is a support tool, not a “trusted colleague”
AI tools (such as chatbots, writing assistants, or code generators) have no awareness of a company’s context, internal rules, or legal obligations.
Anything entered into an AI platform may:
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Be stored temporarily or permanently
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Be analysed to improve the service
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Fall outside the company’s direct control
Golden rule: never share with an AI tool information you would not share in a public space.
2. What types of data should NEVER be shared?
One of the biggest risks is entering sensitive information into public or unauthorised AI tools.
Prohibited or high-risk data
Never enter the following into an AI tool:
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Personal data of customers or colleagues
(full names, contact details, addresses, tax numbers, bank details) -
Access credentials
(passwords, tokens, API keys, MFA codes) -
Confidential company information
(contracts, commercial proposals, pricing, margins, strategies) -
Proprietary or non-public source code
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Information protected by NDAs
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Internal system data, logs, or real databases
Even “just to explain it better” — it is not safe.
3. Beware of the illusion of privacy
Many employees assume:
“No one will see this”
“It’s just a test”
“It’s anonymous, so it’s fine”
In reality:
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Not all tools guarantee that data is not used for training
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Servers are not always located within the European Union
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Not all platforms fully comply with the GDPR
Use only company-approved tools and be familiar with internal policies.
4. Cybersecurity risks associated with AI
Information leakage
An AI-generated response may:
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Repeat sensitive information entered earlier
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Mix real data with fictional examples
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Be accidentally sent to customers or partners
More effective social engineering
AI makes it easier to:
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Write highly realistic phishing emails
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Create personalised messages that appear legitimate
Always be cautious with urgent or unexpected requests, even if they are well written.
Insecure code
For developers in particular:
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AI-generated code may contain vulnerabilities
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It may use outdated or insecure libraries
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It may violate software licensing terms
All code must be reviewed, tested, and validated.
5. Best practices for using AI securely
Use AI for generic tasks
Safe examples include:
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Rephrasing generic text
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Creating document structures
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Generating ideas or lists
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Explaining technical concepts in abstract terms
Always anonymise information
Instead of:
“Customer João Silva from company X has issue Y”
Use:
“A fictional customer from a company in sector X faces issue Y”
Always review the output
Before:
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Sending an email
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Publishing content
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Using code in production
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Making a decision
Final responsibility is always human.
6. AI and GDPR: employees also have responsibility
Improper use of AI may lead to:
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GDPR violations
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Security incidents
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Fines for the company
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Internal disciplinary actions
Even without malicious intent, a simple copy-paste can be enough to cause an incident.
If in doubt, don’t use it — ask IT, security, or compliance teams.
7. The employee’s role in an AI-enabled company
Safe AI adoption depends on everyone:
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Respect internal technology usage policies
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Report risky behaviour
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Share doubts and best practices
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Avoid bypassing rules “to save time”
AI should increase productivity, not introduce new risks.
Conclusion
Artificial Intelligence tools are powerful allies in the modern workplace, but they require awareness, responsibility, and care from every employee.
Using AI securely means:
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Protecting data
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Protecting the company
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Protecting your own work
When used correctly, AI is an accelerator. When used carelessly, it can become a serious risk.
