Before using an AI chatbot, check what information it collects, how it may use or share conversations, how long it keeps them, and what controls protect your account and data. Apply those checks to the exact product, plan, settings, and region you intend to use. Until you understand the terms, avoid entering sensitive information you do not need to share.
Start with the exact chatbot and account you plan to use
Privacy and security can differ between products from the same provider, and between personal and business accounts, subscription tiers, settings, and regions. Read the privacy notice and terms that apply to your account rather than relying on a provider’s general security claims or a description of another version.
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As you review a service, note its product name, account type, region, and any privacy settings you enabled. Check the documentation again if the provider changes its practices; the U.S. Federal Trade Commission (FTC) says privacy commitments apply across a company’s communications, and undisclosed secondary uses or material omissions about data practices can create legal risk (FTC guidance, January 2024).
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“Data is at the heart of AI development,” the FTC notes. Look for a clear account of what the service receives and why. That may include prompts, uploaded files, feedback, account details, and information from connected services.
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- Model improvement: Are conversations or files used to improve or train models? Does the answer depend on a setting, account type, product, or plan?
- Human review: Can employees or contractors review chats, and under what circumstances?
- Service providers and other sharing: Does the provider send data to vendors or disclose it for other purposes? Look for named purposes and exceptions rather than relying on a broad statement such as “we protect your privacy.”
- Connected data: If you link an email account, cloud drive, or other service, identify what information the chatbot can access and what it can do with that access.
- Changes: Check how the provider tells users about changes to these practices and whether you can adjust your choices or stop using the service.
If a notice is vague about whether chats are used for model improvement, reviewed by people, or shared with providers, treat that as unresolved—not as evidence that the practice does not happen. FTC guidance is U.S. consumer-protection guidance, not individualized legal advice; which laws apply depends on the service and circumstances.
Check retention and deletion separately
Look for how long conversations and uploaded files are retained, what happens when you delete them, and whether exceptions apply for security, legal, or operational reasons. A “delete chat” control may not explain whether related records are also deleted or what happens to information already used in a model-improvement process. Seek answers to those questions in the applicable terms or help documentation.
There is no universal retention period for AI chatbots. The FTC’s broader data-security guidance recommends that businesses collect only what they need, protect it, and dispose of it securely (FTC, Protecting Personal Information: A Guide for Business).
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Judge security claims by their scope
“The trustworthiness of AI technologies depends in part on how secure they are,” says the National Institute of Standards and Technology (NIST). Look for information about encryption in transit and at rest, access controls, account-security options, monitoring, incident handling, and independent assessments. If a provider names a certification or audit, check which product, features, and period it covers; a claim about one service does not establish the security of every product from that provider.
NIST frames AI security in terms of confidentiality, integrity, and availability: protecting data from unauthorized disclosure or change and keeping systems usable when needed. It also notes that existing frameworks do not comprehensively address some AI-specific attacks, including evasion, model extraction, and membership inference (NIST, AI Research – Security and Resilience).
One example of why product scope matters: OpenAI says its business products do not train on organization data by default and describes encryption in transit and at rest, audits, and product-specific certifications. These are OpenAI’s statements about its business products, not an independent conclusion about every OpenAI product or other chatbot. Verify the current documentation for the specific product and plan you use (OpenAI, Enterprise privacy).
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Account for risks unique to chatbots
A chatbot can expose information through ordinary account or data-handling failures, but connected features introduce additional paths. If it accepts files, retrieves web pages, or uses tools and integrations, malicious instructions embedded in content may influence what it does. Access to connected accounts can also create consequences beyond the chat itself. And an answer that sounds confident can still be inaccurate, so do not treat output as verified merely because the system produced it.
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When assessing a chatbot with file uploads, retrieval, or integrations, ask what data those features can reach, whether access is limited to what the task requires, and what checks are in place before the system acts on content or returns information. Disable connections you do not need, and be cautious about asking the chatbot to take consequential actions based on untrusted material.
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Minimize sensitive information in prompts and files
Share only what the task requires. Avoid entering passwords, authentication codes, payment credentials, unnecessary health or financial details, confidential work material, or personal data about other people unless there is a clear justification and you have checked the applicable terms and controls. Removing names may not be enough if other details can identify someone.
Data minimization reduces the amount of information at risk if it is retained, misused, disclosed, or exposed. For work or client data, follow your organization’s policies and use only an account explicitly approved for that information.
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Use the same checklist to compare services
Compare candidate chatbots against the same questions rather than treating a single security badge or headline claim as decisive:
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- What data is collected, and for what purposes—including model improvement?
- Do controls differ by product, plan, account type, setting, or geography?
- How long is data retained, what does deletion cover, and what exceptions apply?
- Who else may receive the data, including service providers?
- What account security, access controls, encryption, monitoring, and incident information are documented?
- What does any independent assurance actually cover?
- Can the chatbot access files, external content, or connected services, and what mitigations address related risks?
- Are the disclosures clear and accessible to the people expected to use the service?
NIST’s AI Risk Management Framework is a voluntary resource for developers, users, and evaluators. It treats security, privacy, transparency, and reliability as trustworthiness characteristics to consider across an AI system’s lifecycle (NIST, AI Risk Management Framework).
Take extra care with chatbots aimed at children and teens
For youth-facing or companion-style chatbots, check age restrictions, disclosures for both young users and parents, conversation-data practices, and safety testing. In September 2025, the FTC announced an inquiry seeking information from chatbot companies about data collection and handling, uses and sharing of conversation information, age restrictions, and testing and monitoring. An inquiry is not a finding that every named or other chatbot has violated a rule (FTC announcement, September 2025).
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