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Risks of AI-generated code
AI coding tools are exponentially increasing the quantity of code being created. This code will be more difficult to manage, and strain the review bandwidth of the developers accountable for its quality. The gap between them is the engineering productivity paradox.
The productivity paradox
AI accelerates coding speed, but engineer time to verify it is limited. This gap limits productivity and adds risk.
Lack of trust in AI code
Developers are often concerned about the stability and security of AI-generated code, especially if it’s complex or unfamiliar.
Hidden security flaws
AI models can introduce subtle security vulnerabilities or hard-to-detect errors that expose your organization to risk.
Inconsistent standards
Ensuring that AI-generated code consistently follows your team’s coding standards and best practices is a major challenge.
Secure and verify AI coding with SonarQube
SonarQube helps development teams fuel AI-enabled development and build trust into every line of code, ensuring that AI adoption is controlled and meets the code quality needs of your organization.
Review AI-generated code at scale
Empower developers to review AI generated code while protecting their bandwidth for other work, protecting your organization’s long-term security and code health.
Gain confidence in AI code
Give your developers confidence in the quality, security, and maintainability of the AI-generated code they create or review.
Automatically analyze AI contributions
Automatically flag, analyze, and assure all AI-generated code to ensure it meets your quality standards.
“Sonar helps our development team confidently make both AI-assisted and human-developed code fit for production by reviewing and establishing rules of good programming practices to achieve better code.”
Dario Flores - Technical Quality Specialist, Axoft (Tango Software)
Key capabilities for secure, verified AI coding
AI-ready quality gates
Trusted quality gates for AI-generated code, ensuring it meets the same high standards as human-written code before it can be merged
Automatic scanning
Immediate feedback on AI code quality, security, and compliance in pull requests and branches, directly in the DevOps platform where developers work
Real-time IDE feedback
Developers get instant feedback aligned with team standards in their IDE, allowing them to fix issues as they integrate and review AI code
SAST
Static application security testing that finds critical security vulnerabilities (e.g., injection flaws) that AI models are known to replicate from their training data
Why choose SonarQube for secure, verified AI coding?
Unique assurance of AI code
We are the only solution that can automatically detect and perform a deep, deterministic analysis of AI-generated code.
Visibility into AI adoption
Understand how AI is being used in your organization and measure its impact on code quality and security.
Seamless integration
Apply the same quality and security standards you trust to both human- and AI-written code without any extra configuration.
