4 AI coding risks and how to address them

Developers are increasingly relying on AI coding tools to generate code, detect bugs, and offer suggestions, but this reliance comes with several risks including security vulnerabilities, intellectual property infringement, lack of explainability and transparency, and inconsistent policies around AI-generated code. To mitigate these risks, developers must review, debug, and improve AI-generated code, conduct audits and peer reviews, use tools like Snyk Code to analyze for security vulnerabilities, train teams in potential pitfalls, create clear policies around AI usage, document AI-generated code, and educate stakeholders about these policies.

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