Most AI chat apps keep a running file on you — your words, pictures, clicks and even what the assistant “remembers” between sessions — and there are practical, immediate steps you can take right now to shrink that file or stop it growing.
Background
The recent wave of assistant features —
memories, cross‑chat personalization, “keep activity” toggles and deeper integrations into mail, docs and social apps — has turned ephemeral conversations into persistent data assets for vendors. Vendors argue this data improves usefulness: fewer repetitive explanations, more tailored help and faster workflows. The trade‑off is that those same records can be reused for model training, produce invasive personalization (including ad targeting), and create new attack surfaces for leaks, extortion or regulatory requests. Independent documentation and vendor support pages now give users explicit controls to limit these behaviors — but those controls vary widely by product and are often
default‑on. This article walks through the most widely used consumer assistants, summarizes the specific controls you should change, verifies how those switches actually behave, and weighs the functional trade‑offs for both everyday users and IT teams. It also flags where claims in press coverage were later clarified or where a vendor’s documentation is the only authoritative source.
How these files form and why they matter
- AI assistants keep three distinct layers of data:
- Chat history (the transcripts of conversations).
- Memories / personalization (summaries or extracted facts the assistant stores to tailor future responses).
- Training / telemetry (samples that may be used to improve or fine‑tune models, sometimes involving human reviewers).
- Those layers are used for very different purposes and each has different deletion/opt‑out mechanics. For example, deleting a chat conversation does not always remove a saved memory extracted from it — you frequently have to delete both. That is confirmed in vendor support documentation.
- Beyond privacy: pasted secrets (API keys, passwords, contract text) become high‑value telemetry and may be retained or reviewed. If you paste secrets into a consumer assistant, treat those credentials as compromised and rotate them immediately. Independent security writeups and incident responses echo this urgency.
The single most effective move: use Temporary / Incognito chats
Temporary (or “incognito”) chats are the closest equivalent to a browser’s private mode: they keep the conversation out of your visible history, stop it from updating memories, and — in most vendors’ implementations — prevent that specific chat from being used to train models.
- ChatGPT: the product supports a Temporary Chat toggle that prevents the chat from being saved, from updating memory, and from being used for training. OpenAI documents Temporary Chats as the user control to avoid history and memory usage for a session.
- Claude: Anthropic exposes an Incognito mode so those conversations don’t appear in history or memory, and it’s widely available across plans.
- Gemini: Google added a “Temporary Chat” option and renamed Gemini Apps Activity to “Keep Activity” — keeping that off is equivalent to a private session for long‑term retention.
- Meta AI: as of current documentation, there is no dedicated temporary‑chat toggle inside Meta’s AI app; the practical workaround is to use the assistant while logged out or avoid using the in‑app assistant for anything sensitive. News coverage and help guidance mirror that limitation.
Use temporary/ incognito chats for anything that would cause you regret if it showed up publicly (medical details, passwords, financials, legal plans).
Platform-by-platform controls and exact steps (verified)
Below are the key toggles and the behavior you should expect — each item is verified with vendor documentation and independent reporting where available.
ChatGPT (OpenAI)
What it keeps by default: By default ChatGPT stores chat history, exposes memory features for personalization, and allows account‑wide model training unless you turn it off. OpenAI documents both Memory and Data Controls explicitly. What to change and why:
- Delete past chats: Settings → Data controls → Delete all — this removes visible history but does not necessarily remove saved memories created from those chats; delete memories separately. OpenAI warns that deleted saved memories may linger in backend logs for a short period for safety debugging.
- Turn off Memory: Settings → Personalization → toggle off Reference saved memories. Turning off saved memory prevents the assistant from using your stored facts; it does not auto‑erase existing saved memories unless you delete them.
- Stop training on your stuff: Settings → Data controls → toggle off Improve the model for everyone. This prevents your account’s content from being sampled for model training. OpenAI’s Data Controls page documents that model‑training opt‑outs sync across devices.
- Use Temporary Chat for sensitive queries. Temporary Chat blocks history, memory writes and training for that session.
Why this matters: OpenAI’s model‑training pipeline historically used user prompts for improvement unless a user opted out. Turning off training is low cost to functionality but preserves privacy.
Claude (Anthropic)
What it keeps by default: Claude stores chats and offers memory on paid plans; it asks before using account data to train models in many cases. Anthropic positions memory as optional and provides incognito modes. What to change and why:
- Delete past chats: From the chats list, select All chats and bulk delete. Anthropic’s UI allows bulk operations on chat history.
- Stop model training: Settings → Privacy → toggle off Help improve Claude to stop your content from being used to train models.
- Disable memory (paid accounts): Settings → Capabilities → toggle off Generate memory from chat history if you’re on a paid plan and prefer not to have persistent memory.
Verification: Anthropic documentation and reporting state memory is opt‑in for many users and that incognito chats are provided; enterprise admins can further lock down memory for users.
Gemini (Google)
What it keeps by default: Gemini historically kept chats for a retention period (Google has stated standard retention windows in its activity controls), and in many accounts a portion of activity could be used to improve services. Google’s Gemini Apps support pages document the
Keep Activity control and the temporary chat behavior. Recent product notes show Gemini may keep chats for up to 18 months unless you change auto‑delete settings. What to change and why:
- Auto‑delete or turn off Keep Activity: Gemini → Settings & help → Activity → choose Keep activity off or set auto‑delete interval (e.g., 3 months). Turning Keep activity off prevents chats and uploads from being used to improve models.
- Turn off memory / Personal context: Settings & help → Personal context → toggle off Your past chats with Gemini. This stops the assistant from referencing previous conversations for personalization.
- Gemini in Gmail/Docs: Google says Gemini does not use email/docs content to train models when operating inside Workspace smart features, but workspace admin controls can enforce or disable these features. If you dislike the assistant interacting with your account data, turn Google Workspace smart features off in Gmail settings.
Verification: Google’s Gemini Apps privacy hub and Google blog posts explain the
Keep Activity rename and the temporary chat option; third‑party coverage notes the 18‑month default that some users found surprising.
Meta AI
What it keeps by default: Meta integrates its AI into Instagram, Facebook, WhatsApp and its own app. In a global policy change that took effect in December 2025, Meta began using interactions with its AI tools to personalize content and ads across its platforms in many regions (users in the EU, UK and South Korea were excluded initially). News outlets and vendor notices described a rollout with user notifications sent prior to the change. Meta’s in‑app controls do allow deleting chats and removing public posts and memories, but there is
no single opt‑out that prevents Meta from using AI conversation content for ad personalization. What to change and why:
- Delete past chats: Meta.ai app → Settings → Data & privacy → Manage your information → Delete all chats and media. This removes visible conversation history but does not change Meta’s announced ability to use AI interactions for personalization except by not using the AI at all.
- Remove accidentally public content: Settings → Data & privacy → Manage your information → Remove all public posts to make sure you’re not exposing AI outputs publicly.
- Memory review: Settings → Memory → review & delete memories that Meta AI stored about you.
Caveat and verification: Multiple news outlets reported Meta’s policy change and the inability to opt out while still using Meta AI features; fact‑checks clarified the change applies to AI interactions, not to private DMs, and that sensitive categories would not be used for ad targeting. If you’re in the EU/UK/SK, regional rules may block the change.
Microsoft Copilot
What it keeps by default: Copilot behavior splits by product surface — the consumer Copilot app can save conversations and, in some flows, use chat content for personalization and ad targeting (consumer personalized ads need to be turned off in the Microsoft account). Microsoft 365 Copilot (enterprise) stores
memories in the user’s Exchange mailbox and gives admins powerful controls — though admins can also discover and delete those memories through compliance tools. Microsoft documents the retention model and admin controls in detail. What to change and why:
- Delete chat history (consumer): Microsoft account → Privacy → Copilot → Copilot apps → Delete all activity history. This clears visible history but not necessarily admin‑level copies in enterprise scenarios.
- Stop personalized ads: Microsoft account → Privacy → Personalized ads & offers → set to off to stop ad targeting based on account activity.
- Turn off personalization and memory (Copilot site): Copilot website → profile → Privacy → toggle Personalization and memory off and also Delete memory to remove stored facts.
- Stop model training: Copilot website → Privacy → switch model training (text/voice) to off.
Enterprise note: Tenant admins can enable/disable memory centrally. Memories in M365 Copilot live in the Exchange mailbox and are discoverable by admins via eDiscovery; temporary chats are also visible in Purview for compliance teams. That means corporate usage has a different risk model — never type anything into a corporate Copilot you wouldn’t want your employer to see.
Practical step‑by‑step checklist (15 minutes)
- Open each assistant you use and find the equivalent of: Settings → Data / Privacy / Personalization.
- Turn off model‑training toggles: “Improve the model,” “Help improve X,” “Keep activity” (or set to auto‑delete). Do this for ChatGPT, Claude, Gemini and Copilot.
- Turn off or delete saved memories and custom instructions if you do not want persistent personalization. Delete existing memories if they contain sensitive facts.
- Use Temporary/Incognito chats for sensitive queries. If the app lacks this feature (Meta), avoid the in‑app assistant for sensitive topics or log out first.
- Rotate credentials and secrets if you pasted them into a chat before changing settings. Assume compromise and rotate keys, passwords, and tokens. Independent security guidance recommends immediate rotation.
The trade‑offs and the hard choices
- Functionality vs privacy: The more you strip an assistant of context, the less convenient it becomes. Saved memories reduce repetition. Model‑training toggles sometimes enable improvements that help the assistant handle niche queries. For many users the sweet spot is: disable downstream training and memories for sensitive categories, but keep custom instructions for benign personalization.
- Enterprise vs consumer: Enterprise Copilot and Workspace offerings provide contractual guarantees and admin controls that minimize model training on tenant data — but admins still can discover memories and histories for compliance. For regulated data, use tenant‑bound or dedicated private models, or local inference. Microsoft’s docs show memories are stored in Exchange and accessible via eDiscovery.
- Regulatory patchwork: Some regions (EU/UK/SK) have stricter rules that prevent certain ad uses or require opt‑in; vendors often exclude those regions from wide rollouts. That means your exposure depends on where your account is registered. News coverage of Meta’s ad rollout highlights region‑by‑region exclusions.
Wider risks beyond accidental personalization
- Human review: Some vendors sample chats for human annotation. Turning off training typically reduces sampling risk, but policies and enforcement differ across vendors. OpenAI and Google clearly document sampling and opt‑out mechanics.
- Third‑party exfiltration via browser extensions: A separate but related risk is browser extensions that inject page‑context and exfiltrate conversation content. Security reports recommend uninstalling suspicious extensions, clearing cookies/localStorage for AI sites, and rotating credentials if you used those sites while an extension was present. This is a real attack vector that sits outside vendor settings.
- False memories and hallucinations: Memory systems sometimes misattribute or invent facts. Relying on a bot’s claimed memory of you (for identity decisions, gatekeeping or mental‑health advice) can be dangerous. Independent reporting has documented instances of memory errors causing incorrect identity assertions. Treat remembered assertions with skepticism.
Longer‑term technical options (privacy‑first choices)
- Run models locally: If you need maximum privacy, consider local LLM runtimes (Ollama, local inference stacks) or on‑device capabilities. This reduces cloud telemetry risk but demands compute and may reduce model capability. Community guides and vendor docs outline hardware needs and trade‑offs.
- Use enterprise non‑training plans: For regulated data, negotiate vendor contracts with explicit non‑training, non‑sharing provisions and deletion guarantees.
- DLP / paste‑protection: Use data loss prevention tools that detect sensitive patterns before they reach a chat window (clipboard blockers, enterprise DLP). This reduces human error when employees paste secrets or PHI into an assistant. Industry advisories recommend prohibiting pasting of credentials into consumer AI tools.
What the vendors verify — and what still needs independent confirmation
- Verified: All major vendors provide data‑control toggles (memory, history, training). Vendors’ help pages explain how to disable model training and delete memories or history. OpenAI, Google, Microsoft and Anthropic documentation confirm the existence and placement of these toggles.
- Needs care: Media reports about default flips, rollouts and downstream commercial uses (for example Meta’s ad targeting change) are well‑reported across outlets but sometimes require reading the vendor’s exact blog and privacy pages to reconcile nuance (regional exclusions, sensitive‑category exceptions). For example, multiple outlets reported Meta’s December 16, 2025 change to use AI interactions for ad personalization; fact‑checks clarified the change applies to AI interactions rather than private DMs and noted regional exceptions. Users should verify vendor notices in their account notifications.
- Takeaway: Treat vendor help docs as the authoritative source for how UI toggles behave, and treat independent press coverage as context for policy changes and rollout timing. When in doubt about a claim you rely on for compliance, check the vendor’s official help or legal pages and save the notification emails they send you.
Final verdict: practical privacy posture for everyday Windows users
- Turn off model‑training toggles across services you use. It’s a fast privacy win with minimal downside. Confirm the toggle actually took effect in the service’s Data Controls / Privacy page.
- Use temporary chats for anything sensitive. Export needed content before closing the session.
- Remove saved memories that include identifying or health data. Deleting chat history is often not enough — delete memories and any exported copies too.
- For corporate work, assume tenant admins can access Copilot memory and historic chats; use enterprise controls or avoid consumer assistants for regulated data.
- If you pasted API keys or credentials into any chat, rotate them immediately. Independent security advisories treat pasted secrets as compromised.
The convenience of a chatbot should not cost you control over your most sensitive information. Vendors now offer explicit knobs you can flip — use them. The difference between a casual privacy posture and an explicit one is the difference between a harmless recommendation and a profile that follows you across apps and into ad targeting, compliance headaches or worse. For a short privacy sweep, follow the checklist above and enable Temporary Chats for anything you wouldn’t put on a public timeline.
Conclusion
AI assistants are powerful tools whose usefulness is now tightly coupled with data retention, personalization and training loops. Vendors have made meaningful choices available in settings, but defaults and regional rollouts vary and corporate contexts present different rules. The pragmatic approach for most users: presume chats are recorded; use temporary chats for sensitive topics; turn off training and memory if you value privacy more than incremental personalization; and rotate credentials if you ever paste them into a bot. The controls are there — the job now is to flip the few critical switches and treat AI conversations the way you treat any other sensitive data.
Source: IOL
Your chatbot keeps a file on you. Here’s how to delete it