AI Code Acceptance Rate measures the proportion of AI-generated code suggestions that developers choose to accept and incorporate into their work. It reflects both the quality and relevance of AI outputs and the degree of developer trust in the tool. A low acceptance rate may indicate poor model tuning, misalignment with coding standards, or a need for better prompt engineering practices.
Percentage of AI suggestions accepted. Elite level: 45-54% (Cursor benchmark). Low rates indicate model mismatch or lack of utility.
Individual acceptance rates are stable across scales, but organizational policies and review standards increasingly shape acceptance patterns at larger orgs.