You should avoid entering personally identifiable information, financial details, confidential business data, and medical records into AI chatbots. These tools store, process, and in many cases use your conversations to train their models, meaning sensitive information you type today may persist on third-party servers long after you close the tab. The sections below cover each category of risky data and explain what you can do instead.
What happens to the data you type into a chatbot?
When you type something into an AI chatbot, that text is transmitted to the provider’s servers, stored, and typically used to improve the underlying model. Most major platforms retain conversations by default, sometimes for months or years, and human reviewers may examine a sample of those chats. Deleting a conversation from your account history does not necessarily erase the data from the provider’s systems.
The retention windows vary significantly by platform. Google Gemini saves conversations for 18 months by default and integrates that activity with your broader Google account, including search history and Gmail. ChatGPT’s free tier uses conversations for model training unless you opt out, and even after opting out, OpenAI retains data for 30 days for safety monitoring. Anthropic’s Claude shifted to a hybrid consent model in late 2025: users who did not respond to a policy notification by October 2025 were defaulted to allowing their data to be used for training.
The deeper problem is that once your data is incorporated into a model’s training run, it becomes technically difficult or impossible to fully remove. A Stanford HAI researcher studying six major AI companies concluded that sensitive information shared in a dialogue, including content in uploaded files, may be collected and used for training. Beyond the providers themselves, OpenAI has confirmed it is legally required to share conversation data if subpoenaed, and third-party browser extensions marketed as privacy tools have been found secretly intercepting chats across multiple platforms.
What personal information should never go into a chatbot?
Personal information that can uniquely identify you should never be entered into a consumer AI chatbot. This includes your full name combined with your address, Social Security number, passport or driver’s license details, login credentials, date of birth, phone number, and email address. Each of these data points becomes a liability if the provider suffers a breach or if the data is misused internally.
The risk is not theoretical. Over 225,000 OpenAI account credentials were found on the dark web between 2024 and 2025, stolen by infostealer malware. If your conversation history contains identifying details at the time of a breach, that information travels with the compromised account. Cybercriminals also create fake AI tools specifically designed to harvest personal data through script spoofing and counterfeit browser extensions.
A practical workaround is to anonymize your prompts. Replace real names, workplace details, and identifying context with pseudonyms before submitting a query. If you want help drafting a letter, use a fictional name. If you need advice about a specific situation, describe it in general terms. The chatbot’s response will be just as useful, and you will not have left a trail of personal data on someone else’s server.
Is it safe to enter financial details into an AI chatbot?
Entering financial details into an AI chatbot is not safe. Bank account numbers, credit card details, routing numbers, tax documents, account balances, and investment statements should stay out of any consumer-facing AI tool. Sharing this information creates real exposure to identity theft and financial fraud, and the chatbot’s financial guidance itself carries its own risks.
A June 2026 study published in the Journal of Financial Planning tested seven widely used generative AI platforms on identical personal finance prompts and found significant inconsistencies. Emergency savings recommendations ranged from $19,500 to $37,500 depending on the platform, and some tools produced different recommendations based solely on the demographic profile of the hypothetical user. A 2025 survey by Pearl.com found that roughly one in five U.S. adults who followed financial advice from an AI chatbot reported a financial loss as a result.
The safer approach is to keep financial queries general. Asking a chatbot to explain how a Roth IRA works is low risk. Uploading your actual brokerage statement and asking for portfolio analysis is not. AI chatbots operate without the regulatory guardrails that govern licensed financial advisors, and they are not contractually bound to protect the specific details you share with them.
Can sharing business information in chatbots cause legal problems?
Sharing confidential business information in a public AI chatbot can strip that information of legal protection. Two 2026 U.S. federal court decisions established this directly. In Trinidad v. OpenAI, a court dismissed trade secret claims because the plaintiff had voluntarily disclosed proprietary frameworks to ChatGPT without confidentiality measures, which the court found precluded protection under the Defend Trade Secrets Act. In United States v. Heppner, a judge ruled that documents processed through Anthropic’s Claude were not protected by attorney-client privilege because the platform was not contractually bound to keep them confidential.
The practical exposure goes beyond litigation. Cybersecurity firm Harmonic Security found that more than 4% of workplace AI prompts in Q2 2025 contained sensitive company information, and a LayerX Security report found that over half of content pasted into AI tools includes corporate data. Samsung banned ChatGPT company-wide after engineers pasted proprietary semiconductor source code and internal meeting transcripts into the tool within a single month.
AI chat logs are also potentially discoverable in legal proceedings. Even if a user’s chat history is no longer accessible to them, the AI vendor may be required to produce it under a court order. Law firm Skadden advises sticking to public, non-confidential inputs when using any public AI tool, and several U.S. bar associations, including those in California, Florida, and New York, have issued specific guidance warning lawyers against using consumer AI tools for client matters without explicit consent and robust security guarantees.
What medical and health information is risky to share with AI?
Medical diagnoses, prescription details, mental health disclosures, symptoms, and any information that identifies you as a patient are risky to share with consumer AI chatbots. Most consumer-facing AI tools are not HIPAA-compliant, meaning personal health data shared with them carries no legal protection and can be used for model training, profiling, or exposed in a data breach.
The scale of health-related sharing is larger than many people realize. OpenAI’s own data from late 2025 indicated that approximately 1.2 million ChatGPT users discuss suicide weekly on consumer plans that have no clinical data protection. A separate analysis of Claude conversations found that roughly 2.6% of all chats involved healthcare tasks. Experts at CyberScoop have noted that even where AI providers offer health-focused features, their data security commitments amount to “more of a pinky promise than a legal mandate” unless a formal business associate agreement is in place.
There is also a subtler risk beyond breaches. Large language models can memorize and reproduce rare or unique sequences from their training data. If your health information is used in training, fragments of it could theoretically appear in responses to other users. A hospital chatbot case documented by Paubox in 2026 showed a real-world version of this problem: an AI tool shared patient appointment details and symptoms with third-party analytics providers without consent, constituting a HIPAA violation. Consumer chatbots carry the same structural risk without any of the regulatory accountability.
How do chatbot privacy settings affect what data is stored?
Chatbot privacy settings let you limit whether your conversations are used for model training, but they do not eliminate data storage, processing, or legal retention. Each major platform handles these controls differently, and the defaults are not always privacy-protective. Adjusting your settings reduces one specific risk while leaving others in place.
How to adjust training settings on the main platforms
For ChatGPT, go to Settings, then Data Controls, and toggle off “Improve the model for everyone.” You can also use Temporary Chat mode, which prevents conversations from being saved to history or used for training. For Claude, go to Settings, then Privacy, and turn off “Improve Claude for everyone.” For Gemini, disable “Gemini Apps Activity” in your Google account settings, though Google retains conversations for 72 hours even after opting out, and chats reviewed by contractors may be stored for up to three years.
What paid plans actually protect and what they don’t
Paying for a consumer subscription such as ChatGPT Plus or Claude Pro does not protect your data by default. Conversations on those plans are still used for training unless you manually opt out. The distinction that matters is between consumer plans and business or enterprise plans. ChatGPT Team and Claude Team accounts prohibit training on customer content by contract, not just by a toggle. That contractual protection is meaningfully different from a self-service setting you can toggle on and off.
Opting out of training also does not protect you from legal discovery. A 2025 court order linked to litigation required OpenAI to retain user content for several months, during which deletion requests did not result in full erasure. A 2026 privacy study found that only 27% of users understood how chatbot providers actually handled their data, which means most people are operating with a false sense of control.
What are safer alternatives for handling sensitive information?
Safer alternatives for handling sensitive information with AI fall into three categories: privacy-focused cloud tools, local models, and enterprise-grade platforms with contractual data protections. The right choice depends on how sensitive the data is and what level of risk is acceptable for your use case.
For everyday tasks that do not involve sensitive data, privacy-focused cloud tools offer a reasonable balance. DuckDuckGo’s Duck.ai lets users interact with multiple AI models without an account and without training on prompts. Proton offers a hosted AI assistant with zero-access encryption and a strict no-logs policy. These tools reduce exposure without requiring technical setup.
For genuinely sensitive queries, running an AI model locally is the most secure option. Local models process everything on your own hardware, meaning data never reaches a third-party server. PrivacyTools.io recommends this approach for anything you would not want sitting on someone else’s server. The trade-off is capability: local models are generally less powerful than frontier models like GPT-4o or Claude 3.5.
For businesses handling proprietary data, regulated information, or client confidences, enterprise-grade platforms with on-premise deployment and zero-retention policies provide data sovereignty and audit trails. The contractual protections in plans like ChatGPT Team or Claude Team are a meaningful step up from consumer plans, but they still involve data leaving your infrastructure. For maximum control, on-premise deployment remains the most defensible option.
A tiered approach works well in practice: use general-purpose cloud AI for low-risk queries like research, drafting, and brainstorming, and reserve local or enterprise-grade tools for anything involving financial records, health data, legal strategy, or trade secrets. As AI tools become more embedded in business workflows, AI visibility strategy increasingly includes understanding not just how AI finds your content, but how your content and data interact with AI systems. Building that awareness into your processes now is the practical way to use these tools without unnecessary exposure.
