Last week, we talked about what AI actually is and why it has become such a major topic in business conversations. This week, we need to talk about the part that many people skip over entirely: security.

One of the biggest misconceptions about AI is that it feels private because it looks like a simple chat window. You type in a question, get a response, and move on. Because the experience feels casual, people often forget they are still interacting with an external platform that processes and stores data.

That becomes a serious problem when employees begin entering business information into public AI tools without understanding what happens to the data afterward.

Many public AI platforms improve their systems by learning from the information users submit. Depending on the platform and account type, the prompts, documents, and conversations entered into the system may be stored, reviewed, or used to train future versions of the AI model. In other words, information entered into a public AI tool may not stay private.

This is where businesses can get into trouble very quickly.

Imagine an employee uploads a client contract to “summarize” it, pastes financial information into a chatbot to analyze trends, or enters proprietary company processes to generate documentation faster. In many cases, the employee is simply trying to save time and work more efficiently. The problem is that they may have just shared sensitive company information with a third party without realizing it.

There have already been real-world examples of this happening. In 2023, Samsung engineers reportedly entered confidential source code and internal meeting notes into ChatGPT while troubleshooting technical issues. That information was effectively exposed outside the company’s environment, creating a major security concern.

The issue is not that AI tools are automatically malicious. The issue is that most people do not stop to think about where the data is going once it leaves their computer.

A good rule of thumb is this: if you would not publicly post the information online or send it to an unknown third party, it probably should not be entered into a public AI platform either.

This includes:

– Client records
– Passwords
– Financial information
– Legal documents
– Internal procedures
– Sensitive employee data
– Proprietary business information

Another challenge is that AI does not understand confidentiality the way people do. It cannot determine what information is private, regulated, or inappropriate to share. It simply processes the information it receives and attempts to generate a response.

This is why businesses need clear policies before employees begin using AI tools regularly. Without guidance, employees start making their own judgment calls about what is acceptable, which creates inconsistent security practices across the organization.

That does not mean businesses should avoid AI entirely. These tools can absolutely provide value when implemented correctly and used within the right boundaries. The goal is not fear. The goal is awareness.

Understanding how public AI platforms handle data is one of the first steps toward using these tools responsibly. Businesses that establish clear rules and educate employees early will be in a much better position as AI continues becoming part of everyday operations.

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