Imagine this. It is a Monday morning. David, one of your employees, is facing tight deadlines. He is trying to create a summary from a complicated dataset for an important client report.
In a rush, David turns to ChatGPT. To save time, he copies and pastes sensitive information, including names, account numbers, and transaction history, into the tool. Within seconds, it generates a clean, well-written summary. Feeling relieved, he sends the report and moves on to the next task.
What David does not realise is that this action may have exposed confidential data to external systems. ChatGPT processes input through cloud-based servers.
Unless certain settings are turned off, the data may be stored and used to improve the model. That means private information could be retained, reviewed, or potentially used to train future AI systems.
These kinds of incidents are becoming more common. Generative AI tools are being adopted rapidly across the workplace. They are fast, easy to use, and increasingly powerful. But when employees enter sensitive information without understanding where that data goes, the consequences can affect more than just one person or team.
What Happens to the Data You Paste into ChatGPT?
To understand the risk, we need to know how AI systems like ChatGPT process information. These systems are trained on large amounts of data such as websites, books, and online discussions. This training happens before they are launched. However, many providers continue to collect what users type, especially in the free versions, to improve the system.
Unless users switch off this feature or use the paid enterprise version with privacy settings, the information typed in may be saved temporarily. For example, OpenAI stores user inputs for about 30 days. During this time, human reviewers might check the content to improve the tool’s responses.
Even if the data is not used directly for training, it is still stored in logs. These logs can be accessed or leaked.
There have been real incidents. Reports indicate that Amazon issued a warning to its employees about using ChatGPT in the workplace. In January 2023, the company advised staff not to share confidential internal information with the AI tool after noticing instances where ChatGPT’s responses closely resembled Amazon data. The warning emphasized that input data could potentially be used to train future versions of ChatGPT, raising concerns about the inadvertent exposure of sensitive company information.
This shows the core issue. These tools are not private by default. They operate on cloud-based systems that process data in ways most users do not understand. When sensitive data is involved, the consequences can be serious.
Security and Privacy Are Not Just IT Concerns
When someone puts sensitive data into a public AI tool, the data leaves your internal systems. It goes to the AI provider’s servers. This can break the terms of your client agreements.
Clients may have shared information with you under specific conditions. Those agreements likely did not cover storing the data on an external server.
Even if there is no data breach, just moving the data to another system can still create legal and compliance problems. ChatGPT is not built to handle regulated data by default. It does not come with features like full encryption, audit trails, or compliance certifications for industries like finance or healthcare.
The problem becomes worse because these tools are very accessible. Employees often use them on personal devices or in browsers, which are harder to control. This means even one careless action can bypass the systems your IT team has set up to keep data secure.
Another challenge is the lack of clear information. AI providers do share privacy policies, but these are often difficult to understand. Most employees may not realize that the data they input could be saved, reviewed, or used to train future versions of the AI system. Additionally, there is a lack of transparency around how the data is used in training, leaving many unaware of the potential long-term implications of sharing sensitive information.
Also, the employee may not even realise they are making a mistake. David most likely thought ChatGPT was just a faster way to do his job. Without proper training, many employees will not understand the difference between useful automation and risky behaviour.
Legal and Regulatory Risks
In many sectors, there are strict rules about how sensitive data must be stored and processed.
For example, under GDPR in the European Union, you need proper consent and a legal reason to process personal data. If David pasted data related to EU citizens, his action may count as unauthorised data processing. This could expose the company to fines.
Similarly, under HIPAA in the United States, health records must be handled in specific ways. If a healthcare provider uses ChatGPT to summarise patient histories, and the data is stored on servers that are not compliant, this can also be a violation.
Even if you are in a less regulated industry, contracts often include clauses on data protection.
Breaking those can lead to legal action, loss of business, or penalties. Also, because AI tools use servers across different countries, there is often no control over where the data is stored. That makes it harder to comply with local data laws.
What You Can Do Right Now
There are steps you can take to reduce these risks.
The first is awareness. All employees, not just the IT team, need to understand how AI tools work. They need to know what kind of data is sensitive and why it matters. David did not mean to create a risk. Most people will not. But they need clear instructions to avoid mistakes.
Second, create practical policies. Decide which tools can be used, what kind of data is allowed, and what tools are approved by the company. If your teams rely on AI for daily work, explore safer alternatives. Some enterprise versions of AI tools allow you to switch off data collection and set strict controls.
Third, use technical protections. Set up systems that can detect and stop the sharing of sensitive data. This includes browser settings, alerts for risky actions, and endpoint protection software. These steps will not solve everything on their own, but they add another layer of safety.
Lastly, build a culture of responsibility. Employees should feel comfortable asking questions when they are unsure. Managers should lead by example and use AI tools in a responsible way. That sends a message across the organisation.
Looking at the Bigger Picture
AI tools are becoming an integral part of daily work. They help with writing, research, and data analysis. But they also come with risks if used carelessly.
The problem is not with the tools themselves; they can be invaluable when used properly. The issue lies in how easily sensitive data can be exposed when employees don’t fully understand the systems they’re interacting with. This can create security gaps and damage client trust.
The key message here is that AI tools should not be banned, but used responsibly. Organizations must prioritize educating their workforce, establishing clear guidelines, and implementing technical safeguards to ensure that the adoption of these tools doesn’t inadvertently put client data and the company’s reputation at risk.
How iConnect Can Help
As one of the leading cybersecurity service providers in the region, we can assist you in implementing data protection solutions, security training programs, and advanced monitoring systems to safeguard your information while using generative AI and other tools. With our expertise, you can confidently harness the power of AI, knowing your data is secure and your trust remains intact.
