One of the simplest ways to protect your privacy when using AI tools is to redact sensitive data before sending anything to ChatGPT or other LLMs. Even if a provider has good security practices, you should assume that anything you paste could be logged, cached, or reviewed. So the safest approach is minimizing exposure at the source.
A good habit is to treat prompts like public documents. Remove or mask personally identifiable information (PII) such as names, emails, phone numbers, addresses, customer IDs, or internal project codes. Replace them with placeholders like [CLIENT_NAME], [ACCOUNT_ID], or [COMPANY_X]. The model usually doesn’t need the exact details to give useful advice—context is often enough.
For structured data (logs, spreadsheets, support tickets), automated tools help. Simple regex filters can scrub patterns like credit card numbers or SSNs. For larger workflows, you can use a local script or a private LLM gateway that detects and tokenizes sensitive fields before anything leaves your device. This keeps raw data internal while still allowing the model to process anonymized content.
It’s also worth watching out for indirect leaks. Screenshots, pasted emails, or code comments can accidentally expose confidential info. Redaction should include metadata and attachments, not just visible text.
Ultimately, privacy with AI is less about trusting the tool and more about practicing data minimization. Share only what’s necessary for the task. If the model can answer with abstracted or synthetic data, use that instead. A few seconds of redaction can prevent long-term risks, especially when dealing with client or regulated information.
