GitHub has issued a widespread notification to its users regarding a significant shift in how Copilot data is handled.
Beginning April 24, 2026, the platform will start using interaction data from GitHub Copilot to train its AI models.
This update marks a move toward using real-world developer behavior to refine the accuracy of future code suggestions.
Users are being encouraged to review their privacy settings now to decide whether they want to participate.
What Counts as Interaction Data
According to GitHub, “interaction data” refers to the way you engage with the AI assistant during your coding sessions.
This includes the suggestions you choose to accept, those you ignore, and the specific prompts you enter into Copilot Chat.
It also tracks how you modify suggested code after it has been inserted into your editor.
By analyzing these patterns, GitHub hopes to understand which solutions are most effective for specific programming tasks.
The Mandatory Opt-Out Period
The most notable part of this announcement is that the training feature is enabled by default.
Unless a user manually opts out, their interaction data will automatically flow into GitHub’s training pipeline on the deadline.
This “opt-out” approach is common in the tech industry but often catches busy developers off guard.
You have until April 24 to visit your account settings and manage your preferences before the data collection begins.
How to Change Your Settings and Opt Out on GitHub website
Managing your data preferences is a relatively straightforward process within the GitHub web interface.
First, navigate to your GitHub Account Settings and look for the “Copilot” section in the sidebar.
In the Copilot Settings page, you will find a toggle labeled for “Allow GitHub to use my data for AI model training
.”
Disabling this toggle will prevent GitHub from using your interactions and code snippets for model training purposes.
For users who prefer maximum privacy, it is also worth checking the “Suggestions matching public code” filter.
Implications for Professional and Enterprise Developers
For many developers, the idea of their coding habits being used for training raises immediate security concerns.
Enterprise and Business customers typically have different default protections than individual subscribers.
However, individual developers working on proprietary side projects should be particularly vigilant about these changes.
If you use OpenClaw with GitHub Copilot, you can find more details on our GitHub Copilot Provider Documentation.
Our documentation covers how to securely authenticate and use Copilot models while maintaining control over your local environment.
The Evolution of AI Code Assistants
GitHub’s decision to use interaction data is part of a broader trend in the generative AI space.
As models reach a plateau in public data availability, “human-in-the-loop” feedback becomes the next gold mine for improvement.
The goal is to move beyond simple pattern matching and toward a deeper understanding of developer intent.
While this leads to better tools, it also requires a higher level of transparency between the platform and its users.
Security and Data Sanitization
GitHub has stated that it employs rigorous sanitization methods to remove personally identifiable information (PII).
The company maintains that it does not use your private code directly as training data without explicit permission.
Instead, the focus is on the metadata of the interaction—the “how” and “why” of the coding process.
Even so, the line between interaction data and source code can sometimes feel blurred for those in high-security industries.
Next Steps for Copilot Users
With the April 24 deadline approaching, the best course of action is to perform a quick “privacy audit” of your account.
Take five minutes to confirm that your settings align with your personal or employer’s security policies.
You can also read the full GitHub Privacy Statement for a deeper dive into their data handling practices.
Staying informed about these changes is the only way to ensure your development workflow remains as private as you need it to be.
If you need help configuring your AI models within this workspace, check our Model Configuration Guide.
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