How Private Are Popular AI Assistants?
The widespread adoption of AI assistants like ChatGPT, Claude, and Copilot has raised pressing questions about user privacy.
When you enter a prompt into a chatbot, where does that data go?
Is it stored, analyzed, or used to train future models?
And how do privacy practices differ between free and paid users?
This post summarizes the key privacy trade-offs across several leading AI platforms, drawing from the latest available documentation and real-world usage patterns.
While each provider offers some level of transparency and control, meaningful differences remain in how long your data is retained, whether it’s used to improve models, and what tools you have to manage your data footprint.
Understanding How LLMs Collect and Use Your Data
What Data Is Being Collected
LLMs collect far more than just your prompts. Services like DeepSeek gather profile details (birthdate, email, password), all submitted content (text, audio, prompts, feedback, history, files), and technical data (IP addresses, device identifiers, operating system, keystroke patterns).
This extensive collection helps systems function, personalize experiences, and improve their models through continued training.
The Business Model Behind Your Data
The economics of LLMs create inherent privacy tensions. With billions invested in development, companies monetize free services through aggressive data practices.
Free users typically "pay" with their data, ChatGPT's free version saves all interactions and may use them for model training unless users opt out.
While familiar as an internet business model, this raises unique concerns given the personal nature of LLM conversations.
Key Dimensions of Privacy
Here are the main factors we examined:
Data Retention: How long are your chats stored on the platform’s servers?
Training Usage: Is your data used to train or fine-tune models?
Opt-Out Controls: Can you prevent your data from being used for training?
Data Export: Can you download your data or conversation history?
Audit Logging: Can you view or track what was accessed or shared?
Free vs. Paid: The Privacy Gap
One of the clearest patterns in our research is the privacy divide between free and paid (especially enterprise) plans.
ChatGPT (OpenAI)
Free/Plus: By default, your conversations may be used to improve OpenAI’s models, though you can opt out via settings. Chats are stored until deleted and purged from servers within 30 days. You can export data manually. No audit logs.
Team/Enterprise: Conversations are not used for model training. Enterprise plans include compliance APIs that allow admins to retrieve logs and manage data retention.
Claude (Anthropic)
Free/Pro: Claude does not use your chat data to train its models. Conversations can be deleted and are purged within 30 days. Data export is available via settings. No audit logs.
Enterprise: Offers additional admin tools and retention controls.
Gemini (Google)
Free: By default, Gemini conversations may be reviewed by humans to improve product quality. You can opt out in your settings. Conversations are stored for up to 72 hours unless you delete them manually. Export is available via Google Takeout. No audit logs are offered at this tier.
Enterprise (Gemini for Workspace): In enterprise and education editions, user interactions with Gemini are not used for training or reviewed by humans. Admins gain access to robust controls including data governance, audit logs, and enforced retention policies, integrated with Google Workspace tools.
Microsoft Copilot
Free/Home: Prompts and responses are logged per Microsoft’s standard privacy policies but are not used to train the underlying models. Users can view and manage Copilot activity via the Privacy Dashboard.
Enterprise (Microsoft 365 Copilot): Chats are stored in user mailboxes and subject to Microsoft Purview policies. Full audit logging and admin controls are available.
xAI Grok
Free: User inputs may be used to improve the model unless you opt out or use Private Chat mode. Conversations are stored until deleted, with Private Chats purged after 30 days. No export tool or audit logs.
Enterprise: Offers a separate data boundary and excludes enterprise data from training.
DeepSeek
Free: Data is retained indefinitely unless deleted. Prompts may be used to improve DeepSeek’s models, and no opt-out is available. No export or audit tools.
Enterprise: Policies depend on deployment (e.g., via AWS Bedrock).
Perplexity AI
Free/Pro: Does not use user data to train models. Conversations are stored but can be deleted. Files auto-expire after 7 days. No export tool for chat history.
Enterprise Pro: Adds incognito mode, admin alerts, and security monitoring. Still no training on user content.
Privacy Comparison (Free Tier): Most to Least Private
Privacy Comparison (Paid Tier): Most to Least Private
AI Privacy: Protecting Your Data in a Digital World
Privacy Controls & Opt-Outs
Many AI platforms allow users to opt out of model training, though the visibility and effectiveness of these settings vary. In ChatGPT, for instance, disabling "Improve the model for everyone" (Settings → Data Controls) prevents data from being used for training, but it doesn’t erase it entirely. Some data may still be stored for system monitoring or abuse prevention.
Temporary Chats: A Privacy Trade-Off
For sensitive queries, ephemeral chats, like ChatGPT’s Temporary Chats, automatically delete after 30 days and exclude data from training. The downside? You lose access to past conversations.
Data Deletion & Ownership
AI platforms often provide options for exporting data and deleting accounts, but fully erasing data is tricky, especially if it has already influenced a model.
Privacy Risks: Breaches & Memorization
Even secure systems can fail:
DeepSeek’s 2025 Exposure: A misconfigured database leaked over 1M log entries, exposing user information.
Training Data Leaks: Large language models (LLMs) sometimes memorize sensitive details, including emails or confidential texts, which can unexpectedly resurface in responses.
Samsung banned employees from using ChatGPT and similar AI tools after an engineer leaked internal source code, raising concerns about data security and the risk of confidential information being stored or shared externally.
Free vs. Paid AI: The Privacy Myth
Paying for AI doesn’t necessarily mean better privacy. While premium tiers offer more features, core privacy controls, like opt-outs, are usually available to all users. The real difference? Subscription models reduce incentives to monetize user data.
Enterprise plans provide better privacy and administration features, but paid consumer plans like ChatGPT Plus usually have the same privacy as free versions, unless noted.
How to Stay Protected
Take control of your privacy with these key steps:
Adjust settings immediately: Disable model training where possible and shorten data retention periods.
Avoid oversharing: Never input sensitive personal or work-related information.
Use ephemeral chats: For high-risk queries, opt for temporary conversations that auto-delete.
Compartmentalize: Separate accounts for different purposes.
Stay informed: AI policies evolve quickly, review your settings regularly.
Corporate & Enterprise Risks
While AI tools enhance productivity, they also pose significant risks—potentially exposing intellectual property, customer data, or confidential plans.
Some companies ban sharing proprietary code or sensitive details with public AI platforms.
For high-stakes data, private LLM deployments, hosted in-house, offer greater security but require substantial resources.
The Privacy Paradox
AI provides immense utility, yet comes with unavoidable exposure risks. The best approach? Use selectively, share minimally, and lock down privacy settings.
As AI evolves, expect tighter regulations and increased competition on privacy features. For now, staying informed and proactive is the best way to keep your data secure.
Navigating the AI Frontier with Confidence
The world of AI assistants is undeniably exciting, offering unprecedented capabilities. However, as this overview shows, convenience comes with a critical need for data privacy awareness.
Understanding how platforms like ChatGPT, Claude, Copilot, and others handle your data, from retention policies to their use in model training, is the first step towards responsible AI adoption.
While individual users can leverage opt-outs and mindful sharing, businesses face a more complex challenge: balancing innovation with the imperative to protect intellectual property, customer data, and confidential information.
The "privacy paradox" is real, but not insurmountable.
How NorthBound Advisory Can Help:
Navigating this intricate and rapidly evolving AI landscape requires expertise. At NorthBound Advisory, we specialize in helping organizations:
Develop AI Governance & Usage Policies: Crafting clear guidelines on acceptable AI use, data handling, and risk mitigation.
Assess AI Tooling & Vendor Risks: Evaluating platforms based on your specific security, compliance, and privacy requirements.
Implement Data Protection Strategies for AI: Ensuring that your adoption of AI aligns with data privacy best practices and regulatory obligations.
Stay Ahead of the Curve: Providing insights into emerging AI trends, ethical considerations, and privacy-enhancing technologies.
The journey with AI is transformative. By arming yourself with knowledge and partnering with trusted advisors, you and your organization can harness the power of these tools confidently and securely. The future of AI is not just about capability, but also about responsible stewardship of the data that fuels it.
To explore this topic a bit deeper, checkout a 8-minute Podcast from Rick and Amanda as they explore this Blog in greater depth.
