Who Owns the Code?
This is one of the most unsettled areas in AI-assisted engineering, and the answer matters for your employer.
Large Language Models are trained on billions of lines of public code — from GitHub repositories, StackOverflow, documentation, and open-source projects. That code includes software licensed under terms like the GPL (GNU General Public License), which is a "copyleft" license. Copyleft means: if you use GPL-licensed code in your software, your software must also be released under the GPL. For a company shipping proprietary software, this is a serious legal problem.
The Risk:
If an AI assistant generates a code snippet that is substantially identical to a GPL-licensed function it memorized during training, and you paste that snippet into your company's proprietary codebase, you may be incorporating GPL-licensed code without complying with the license terms. The AI does not warn you. It does not cite sources. It just produces the code.
This is not a theoretical risk. GitHub Copilot has been demonstrated to reproduce verbatim code from public repositories in certain conditions.
Mitigation Strategies:
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Enable duplication filtering: GitHub Copilot has a setting called "Block suggestions matching public code." Enable it. This instructs the model to avoid generating suggestions that closely match indexed public code, forcing it toward original synthesis.
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Apply the StackOverflow standard: Treat AI-generated code the same way you treat code copied from StackOverflow — read it, understand it, and adapt it to your context. Do not blindly copy large blocks. If you understand the code well enough to have written it yourself, you have effectively created a new implementation.
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Never paste secrets into AI prompts: This deserves its own rule. Do not paste API keys, database credentials, internal hostnames, or customer PII (Personally Identifiable Information — names, emails, financial data) into any AI chat interface. Even if the vendor promises not to use your data for training (as enterprise tiers of Copilot and Cursor typically do), the data is still transmitted to a third-party server. Treat the prompt window as a public forum.
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Use enterprise tiers for sensitive work: Consumer-tier AI tools (free ChatGPT, free Copilot) may use your inputs to improve the model. Enterprise tiers contractually prohibit this. If your company handles sensitive data, use the enterprise tier or a self-hosted model.
A common interview question at companies with strong legal/compliance cultures is: "What are the risks of using AI coding assistants in a production engineering environment?" Weak answers focus only on code quality. Strong answers cover three dimensions: (1) legal/licensing risk from memorized training data, (2) security risk from AI-generated vulnerabilities, and (3) data privacy risk from pasting sensitive information into third-party prompts. Mentioning that you know how to mitigate each — duplication filtering, code review, and data obfuscation — signals maturity.
Key Point: AI-generated code carries the same licensing obligations as human-written code. The fact that a machine wrote it does not create a legal exception. Treat it with the same scrutiny you would apply to any third-party code you are incorporating into a commercial product.