How to Check If Code Is AI Generated: 7 Reliable Methods

Why Knowing How to Check If Code Is AI Generated Matters

The rise of tools like GitHub Copilot, ChatGPT, and Amazon CodeWhisperer has transformed how code is written. While these AI coders offer speed and convenience, they also introduce risks, such as:

• Plagiarism in educational or professional environments

• Security vulnerabilities due to AI hallucinations

• Loss of code originality or copyright concerns

That's why understanding how to check if code is AI generated isn't just a technical skill—it’s a digital literacy requirement in 2025.

1. Use AI Code Detectors Like GPTZero and Copyleaks

Several platforms have emerged to help identify whether content was produced by an AI model. GPTZero and Copyleaks AI Content Detector now support code input and can provide a confidence score. These platforms analyze structure, syntax, and predictability to assess if code likely came from a large language model.

2. Analyze Code Style and Naming Conventions

One easy way to tell if code is AI generated is by examining the style. AI-generated code tends to use:

• Generic variable names (e.g., data, temp, result)

• Verbose or overly detailed comments

• Consistent indentation and formatting

AI models are trained to follow best practices rigidly. If the code looks "too perfect," it might be AI generated.

3. Check for Lack of Contextual Integration

A common trait in AI-generated code is a lack of context awareness. For example, the code might:

• Ignore surrounding business logic

• Hardcode values instead of using variables

• Duplicate functionality that already exists elsewhere in the codebase

Developers naturally reuse and reference existing functions. AI tools, however, often generate standalone logic without integration.

4. Review Git Commit History

Platforms like GitHub track every commit. By analyzing metadata, you can sometimes check if code is AI generated by identifying signs such as:

• Commits made within seconds/minutes of each other

• High volumes of code written by a single contributor in a short span

• Presence of known AI-generated commit messages (e.g., “initial commit with sample login function”)

These clues are not definitive, but when combined with other methods, they strengthen your detection strategy.

5. Use AI-Powered Static Code Analyzers

Static analysis tools such as Snyk, DeepCode (by Snyk), and SonarQube can sometimes spot AI-generated patterns. These platforms flag:

• Redundant logic or unused variables

• Code smells that often stem from templated AI outputs

• Unusual control flow that a human might optimize differently

6. Observe Comment Patterns and Language

AI-generated code often contains:

• Overly formal or mechanical explanations

• Unnecessary comments for obvious lines of code

• Comments that describe what rather than why

Humans tend to write purpose-driven comments. AI tends to explain line-by-line, especially when using models like ChatGPT or Claude to generate code.

7. Cross-Reference with Known AI Code Repositories

Want to check if code is AI generated with higher certainty? Compare the code in question to outputs from known AI tools using:

• GitHub Copilot Labs examples

• Stack Overflow discussions citing AI usage

• OpenAI Cookbook sample code for GPT-based tools

If the structure or logic matches common Copilot or GPT outputs, the code may indeed be AI-generated.

Bonus: Ask the Developer Directly

If you're reviewing a pull request or grading an assignment, and still unsure how to tell if code is AI generated, ask the author about their process. A developer who wrote the code manually can usually explain their logic. Someone relying on AI might struggle to provide rationale or technical insight.

Recommended Tools to Help Detect AI Code

How to Stay Ahead in an AI-Coded World

As AI continues to evolve, so will its ability to mimic human coding practices. Staying informed about how to check if code is AI generated helps you maintain high standards in your work or organization. By combining tools, code intuition, and peer review, you can spot AI-generated code accurately and responsibly.

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