GitHub has rolled out AI-powered code reviews for Copilot users, allowing developers to receive automated feedback on pull requests.
The feature, now in public preview, extends GitHub Copilot’s role beyond code suggestions to actual review analysis. While designed to streamline development workflows, GitHub emphasizes that Copilot does not approve or reject pull requests, reinforcing that human oversight remains necessary.
Developers using Copilot Individual, Business, or Enterprise plans can now select the AI assistant as a reviewer when opening a pull request.
The system evaluates code changes and provides inline comments suggesting improvements. Copilot always leaves a ‘Comment’ review, not an ‘Approve’ or ‘Request changes’ review, ensuring that AI-assisted reviews remain advisory rather than authoritative.
How AI Code Reviews Work
Copilot’s review system assesses pull requests by identifying best practice violations, structural inconsistencies, and areas where refactoring could improve readability.
It can flag repetitive code, offer formatting corrections, and suggest alternative approaches for optimization. Developers can review Copilot’s suggestions and choose whether to implement them.
For enterprise users, GitHub has introduced customizable AI policies that allow organizations to define coding standards. These policies guide Copilot’s assessments to ensure that recommendations align with internal best practices. Teams can enforce naming conventions, highlight security concerns, and prevent the use of deprecated functions.
Before launching publicly, GitHub tested AI code reviews in a private preview in December 2024. Early testers noted that while Copilot effectively flagged basic errors, it sometimes misinterpreted complex logic, leading to incorrect suggestions.
The public preview aims to refine these capabilities by incorporating broader developer feedback.
AI Code Reviews Still Need Human Oversight
Despite its ability to accelerate code reviews, Copilot’s AI has notable limitations. While it can spot redundant code, minor errors, and inconsistencies, it does not fully understand broader architectural decisions, security vulnerabilities, or business logic.
Developers testing the AI review system during its private preview reported cases where Copilot misinterpreted complex logic, sometimes flagging perfectly valid code while missing deeper structural issues.
One of the concerns surrounding AI-generated code is the potential for unintentional copyright infringement.
To address this, GitHub last December launched Code Referencing. This feature flags AI-generated suggestions that closely resemble publicly available code, helping developers verify whether they are incorporating legally compliant snippets into their projects.
GitHub Copilot’s Expanding Role in AI-Assisted Development
GitHub Copilot’s evolution into AI-driven reviews is part of Microsoft’s broader AI strategy. In December 2024, GitHub introduced a free-tier version of Copilot for Visual Studio Code, providing limited access to AI-generated code completions.
While the free plan does not include AI code reviews, it signals Microsoft’s intent to expand AI-powered coding tools to a wider audience.
Further AI advancements came in Visual Studio Code 1.97, which introduced Next Edit Suggestions, enabling Copilot to predict modifications based on a developer’s coding patterns.
This complements AI-assisted reviews by offering proactive recommendations before a pull request is even submitted.
GitHub has also expanded Copilot to Apple’s Xcode, bringing AI-driven development tools to Swift and Objective-C developers. While AI reviews are not yet available on Xcode, this expansion suggests that GitHub is positioning Copilot as a cross-platform AI coding assistant.
Microsoft’s AI push extends beyond IDEs. With Windows Terminal AI Chat, developers can now get AI-driven command-line assistance in Windows.
While the feature does not execute commands, it provides syntax guidance and troubleshooting support, reinforcing Microsoft’s commitment to AI-assisted software development.
Competition Among AI Coding Assistants
GitHub Copilot is not the only AI-driven coding assistant on the market. In February 2025, Google introduced Gemini Code Assist, a direct competitor that offers significantly higher free-tier allocations.
Gemini provides up to 180,000 completions per month compared to Copilot Free’s 2,000 completions, making it a more attractive option for developers looking for AI assistance without a paid subscription.
Another key difference is platform support. While GitHub Copilot is deeply integrated into Microsoft’s development ecosystem, Gemini Code Assist supports a wider range of IDEs, including JetBrains, Visual Studio Code, and GitHub itself.
This flexibility could make Google’s offering more appealing to developers who prefer working outside Microsoft’s toolchain.
The growing competition in AI-assisted development tools may pressure GitHub to reconsider its pricing model. While Copilot’s AI code reviews add value for paying subscribers, Microsoft’s decision to limit the feature to paid users could restrict adoption among smaller teams and independent developers.
If Google’s free-tier model proves popular, GitHub may need to expand Copilot’s free-tier capabilities to maintain its competitive edge.
The Future of AI-Assisted Code Reviews
GitHub’s introduction of AI-driven code reviews marks an important step in the automation of software development workflows. However, the technology is not yet capable of fully replacing human reviewers.
While Copilot can speed up the process by catching low-level issues and providing quick fixes, it still struggles with high-level decision-making that requires an understanding of project-specific requirements.
Microsoft’s broader AI strategy suggests that Copilot will continue evolving, integrating deeper into GitHub’s pull request workflows. Future updates may bring improvements in AI’s ability to detect security vulnerabilities, analyze performance optimizations, and better adapt to specific coding patterns.
Whether developers fully embrace AI-driven reviews will depend on how well these systems can balance automation with reliability.
