Urgent: How to Stop GitHub Copilot from Using Your Code for AI Training (Before April 24)

TL;DR

GitHub will start using your Copilot interaction data for AI model training on April 24, 2026. Your code snippets, chat conversations, and acceptance decisions become training data unless you manually opt out. Change your settings at github.com/settings/copilot before the deadline to keep your code private.

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Introduction

Your Copilot workflow may become training data for future AI models.

On April 24, 2026, GitHub's updated Copilot policy takes effect. Under this change, Microsoft and GitHub can use Copilot interaction data—including code snippets, debugging questions, and refactoring requests—to train future models. This may include proprietary code from private repositories.

If you manage a team or work with sensitive codebases, review your Copilot settings before the deadline and share the opt-out steps with your engineering lead.

What Changed in GitHub's Copilot Policy

GitHub describes the update as a way to “personalize and improve” Copilot experiences. The relevant change is the use of Copilot interaction data for training future AI models.

Policy Timeline

April 24, 2026 is the enforcement date. After that date, GitHub assumes consent unless you manually opt out in your account settings.

GitHub refers to the data as “interaction data.” In practice, this can include the code and context you provide while using Copilot.

What GitHub Collects

Data type	What it includes	Privacy risk
Code snippets	Code you write or modify with Copilot assistance	Proprietary algorithms, business logic, API integrations
Chat conversations	Context from Copilot Chat sessions	Architecture decisions, debugging workflows, system design
Acceptance decisions	Suggestions you accept or reject	Signals about what your team considers “good” code
File context	Surrounding code used to generate suggestions	Database schemas, authentication flows, internal APIs
Correction patterns	How you modify Copilot output	Coding standards and security practices

This data can train GitHub's next-generation models. Once code patterns are incorporated into model weights, they may influence suggestions provided to other users.

Why the Default Matters

GitHub asks users to review the update and manage their preferences. That means privacy protection requires an explicit action from each user.

After April 24, the default is opt-in.

For development teams, this makes Copilot privacy a configuration-management task rather than an individual preference. Treat it like any other security or compliance control: document it, verify it, and enforce it where possible.

Step-by-Step: Opt Out of GitHub Copilot Data Collection

Opting out takes only a few minutes. Complete these steps before April 24.

Method 1: Individual Account Settings

1. Open Copilot settings

1. Go to github.com.
2. Click your profile icon in the top-right corner.
3. Select Settings.
4. Select Copilot in the left sidebar.

2. Disable AI model training data usage

1. Scroll to the Privacy section.
2. Find the option labeled Allow GitHub to use my data for AI model training.
3. Disable the option.
4. Confirm that the setting remains disabled.

3. Confirm the change

• Allow up to 30 minutes for the preference to take effect.
• Restart your code editor if you want the updated setting to apply immediately.

Method 2: Organization-Wide Settings

If you administer a GitHub organization, configure this at the organization level so individual developers do not need to manage it separately.

1. Open organization settings

1. Go to your organization’s GitHub page.
2. Click Settings in the organization navigation.
3. Select Copilot from the left menu.

2. Configure the policy

1. Find Copilot data usage policies.
2. Select Disable interaction data collection for all members.
3. Save the change.

3. Communicate the policy

After applying the setting:

• Document the policy in your internal wiki or security handbook.
• Notify developers in Slack or email.
• Add the setting to onboarding and offboarding checklists.
• Record the decision in your compliance or vendor-management documentation.

Verification Checklist

There is no CLI command for verifying this preference. Use the GitHub UI and your internal controls instead:

1. Confirm the training option is unchecked in Copilot settings.
2. Capture a screenshot or configuration record for compliance evidence.
3. Review GitHub data-download options:
   Settings > Privacy > Download your data
4. Recheck organization-level Copilot policies after administrative changes.

Important: Opting out does not delete data already collected. It only prevents future collection from the time you change the setting.

Enterprise and Compliance Considerations

If your team works in a regulated industry or handles sensitive customer data, review this policy change with security, compliance, and legal stakeholders.

Industries That Need Extra Scrutiny

Industry	Regulation	Concern
Healthcare	HIPAA	PHI exposure through code comments or variable names
Finance	SOC 2, GDPR	Customer transaction logic and PII handling patterns
Government	FedRAMP, ITAR	Classified system architecture and security protocols
Enterprise SaaS	Customer contracts	Proprietary algorithms and competitive advantages

Questions for Legal and Compliance Teams

Before April 24, schedule a review and answer these questions:

• Does our current MSA with GitHub address AI training data usage?
• Do customer contracts prohibit sharing code with third-party AI services?
• Could source code, comments, variable names, or API schemas expose regulated data?
• What liability exists if proprietary code patterns surface in competitor suggestions?
• Do we need an enterprise agreement with explicit data restrictions?

GitHub Enterprise Options

GitHub Enterprise customers may have additional negotiating options. Ask your GitHub account representative about:

• Contractual guarantees against training data usage
• Private model instances for regulated workloads
• Enhanced audit logging for compliance reporting
• Custom data-retention policies

Apidog for API Development Privacy

For teams building and testing APIs, privacy extends beyond code completion. Apidog provides a privacy-first alternative to cloud-based API development tools:

• Local-first architecture: API specifications stay on your machine.
• No training on customer data: Apidog does not use API definitions to train models.
• Self-hosted options: Maintain data sovereignty for regulated workloads.
• Internal collaboration: Share specifications with your team without third-party exposure.

When evaluating AI-powered development tools, ask:

Where does my data go, and how is it used?

The answer should be documented, clear, and contractually binding.

What Happens If You Do Not Opt Out

If you remain opted in after April 24, your Copilot interaction data can enter GitHub's training pipeline.

Your Code Enters the Training Pipeline

• Interaction data is collected in batches.
• You may not receive a notification when your data is used.
• There may be no mechanism to request deletion after data is incorporated into models.

Potential Exposure Scenarios

• A competitor prompts Copilot with similar context.
• A model generates suggestions resembling your code or implementation patterns.
• There is no audit trail showing which training data influenced a generated output.

Compliance Complications

• Customer audits may flag AI training data usage.
• Regulatory inquiries may require data mapping that you cannot provide.
• Contractual violations may trigger breach-notification requirements.

Can You Opt Out Later?

Yes, but there are limitations:

Data category	Result after opting out
Future data	Collection stops going forward
Historical data	Data may already be incorporated into models; deletion is not guaranteed
Model weights	Even if data is deleted from datasets, models may retain learned patterns

The most direct approach is to opt out before April 24.

Conclusion

GitHub's Copilot policy change takes effect on April 24, 2026. Your interaction data—including code snippets, chat conversations, and acceptance patterns—can become training material for GitHub AI models unless you manually opt out.

Take two minutes to review your Copilot settings, document the decision for your team, and verify organization-level controls where applicable. For API teams that need privacy-focused tooling, explore Apidog: an all-in-one API development platform designed to keep API specifications private by default.