If You Don’t Opt Out by April 24, Will GitHub Train on Your Private Repos?

# If You Don’t Opt Out by April 24, Will GitHub Train on Your Private Repos?

Yes—for many individual Copilot users, GitHub can use what you do with Copilot on private repos for AI training by default after April 24, 2026, unless you opt out. The key nuance is that GitHub says it won’t take your private repositories’ stored source code (“at rest”) and dump it wholesale into training. But the company’s update explicitly covers Copilot interaction data—and those interactions can include code snippets and associated context that originate from private-repo work.

The quick answer (and who it applies to)

Starting April 24, 2026, GitHub flips the default for Copilot Free, Copilot Pro, and Copilot Pro+ individual accounts: Copilot interaction data will be available for AI model training unless you change a setting to decline.

If you’re using an organization or enterprise account governed by a Data Protection Agreement (DPA), GitHub says you’re not included in this default training-use change. In other words: this policy shift targets individual Copilot accounts, not org/enterprise setups covered by existing contractual protections.

That boundary matters, because many developers mix contexts—using a personal Copilot subscription while working on code that belongs to an employer or client.

What GitHub actually announced (the facts)

GitHub published a changelog entry on March 25, 2026 titled “Updates to our Privacy Statement and Terms of Service: How we use your data”, pointing users to updated policy documents and explaining how Copilot-related data may be used going forward.

The practical change is simple but consequential:

• Effective date: Default training-use behavior starts April 24, 2026 (announced March 25).
• Scope: Copilot Free/Pro/Pro+ individual accounts.
• Excluded from this default rule: Organization and enterprise accounts governed by existing Data Protection Agreements.
• Data described for training: GitHub’s description centers on “inputs, outputs, code snippets, and associated context” from Copilot interactions.

Reporting from multiple outlets summarized the same core point: GitHub will begin using interaction data for model improvement/training by default for eligible individual users, with an opt-out available in settings.

What counts as “Copilot interaction data”?

GitHub’s own framing—inputs, outputs, code snippets, and associated context—covers the core loop of using Copilot:

• Inputs: What you provide to Copilot during use (for example, prompts or code you type into the Copilot interaction).
• Outputs: What Copilot returns (suggestions, completions).
• Code snippets: Pieces of code involved in the exchange.
• Associated context: Additional contextual information tied to the interaction (the policy wording matters here because “context” can be broad).

Put plainly, this isn’t just “telemetry” in the narrow sense of clicks and timings. It’s the substance of Copilot sessions: what you asked, what you showed it, and what it produced.

This is also why developers who are already nervous about AI assistants have been exploring more controlled approaches—see our related coverage on the shift toward sandboxing and on-device tooling in Privacy Push Drives Sandboxed, Local AI Agents.

So… will GitHub train on “private repo content”?

GitHub draws a distinction that’s easy to miss:

• Private repository source code “at rest” (the stored code sitting in your repo) is not being newly treated as training data under this update.
• But Copilot interactions can include snippets or context derived from that private code, because you use Copilot while working in those repos.

That means “GitHub won’t scrape my entire private repo” and “GitHub might still receive private code fragments through Copilot usage” can both be true at the same time.

In practice, if you invoke Copilot while editing proprietary code—and your account is an eligible individual account—then the interaction-derived pieces of that session may be available for training by default after April 24 unless you opt out. This is the crux of the nuance: the repo itself isn’t being bulk copied, but your workflow can still surface meaningful parts of it.

Why It Matters Now

This is a time-sensitive change because it flips the default. From April 24 onward, doing nothing means your eligible individual Copilot interactions can be used for training. For developers who want the opposite outcome, there’s a short, clear to-do: find the setting and opt out.

It also matters because it represents a meaningful policy direction. The research brief notes a historical arc: Copilot initially used user data for training, then GitHub moved away from using user content in a prior shift—and now this 2026 update returns to a default training-use posture for individual accounts (with opt-out).

Finally, the response isn’t happening in a vacuum. Coverage has emphasized concerns familiar in modern AI debates: opt-out defaults, potential product nudges, and ongoing disputes over what counts as permissible training data. Those same anxieties show up in adjacent areas like synthetic media; for more context on how quickly “input → model behavior” pipelines can evolve, see Today’s TechScan: Deepfakes, Supply‑Chain Intrigue, and Unexpected Hardware Turns.

Practical risks and considerations for developers

The most concrete risk is unintended exposure of proprietary or sensitive code fragments. Even if GitHub isn’t pulling your whole repo, Copilot interactions can still contain:

• A snippet you pasted into a prompt
• A portion of surrounding code included as context for a completion
• The model’s output, which might echo or transform your inputs

That can create compliance and IP headaches when the account is personal but the code belongs to an employer. DPAs may protect org/enterprise accounts, but they don’t automatically protect a developer who’s using a personal Copilot plan on work code.

The flip side is important too: this isn’t a claim that GitHub is wholesale ingesting every private repository file. The risk is more granular—but granular leaks can still be meaningful.

How to protect your private code (step-by-step)

1. Opt out in settings (before or after April 24):

Go to your GitHub account settings for Copilot/privacy controls and disable the option that allows GitHub to use your Copilot data for model training (often described as “use my Copilot data for model training” or equivalent).

1. Use organization/enterprise-provided accounts for sensitive work:

If your employer offers Copilot through an org/enterprise plan governed by a Data Protection Agreement, prefer that for proprietary codebases.

1. Reduce sensitive context in Copilot interactions:

For high-risk files or secrets-adjacent areas, limit what you paste or ask Copilot to reason over. Treat Copilot prompts like a channel where snippets may be retained for training unless you’ve opted out.

1. Update team guidance:

If you lead a team, document whether personal Copilot accounts are allowed on work repos, and align onboarding and policy with the new default behavior.

What to Watch

• Retention and deletion details for interaction data already collected (and any clarifications GitHub adds in future privacy updates).
• Whether GitHub introduces UX nudges that steer individual users toward leaving training enabled.
• How enterprises adjust internal guidance about developers using personal Copilot accounts on work projects—even if enterprise accounts are excluded by DPAs.

Sources: github.blog ; techspot.com ; tech2geek.net ; theregister.com ; roboin.io ; howtogeek.com