What is AI-Assisted Code?
Code produced with help from AI coding tools like Copilot, Cursor, or Claude.
Definition
AI-assisted code is code written with help from AI tools — autocomplete, chat, or agentic assistants such as GitHub Copilot, Cursor, Claude Code, or aider. Measuring its impact means comparing AI-influenced work against the rest on both speed and quality.
How it’s measured
Adoption can be detected from commit trailers and co-authorship metadata, and from vendor usage APIs (seats, acceptance rates, spend). Impact is best measured by comparing AI-heavy work to non-AI work on cycle time, PR health, and maintainability — ideally with a difference-in-differences design.
What good looks like
There is no industry benchmark yet. The honest question is directional: are AI-adopting teams shipping faster without a faster rise in tech debt and duplication? Treat findings as association, not proof of cause.
Why it matters
Engineering leaders are spending real money on AI tools and being asked whether it works. Measuring AI-assisted code — speed and the quality counterweight together — turns that from a gut feel into evidence.
Related terms
Measure AI-Assisted Code automatically
DXSignal computes this and every other delivery, quality, and experience metric from the tools you already use.
Get Started Free