2026 AI Coding Usage Survey Template

An AI coding usage survey is a structured questionnaire that measures how developers adopt, use, and evaluate AI-assisted coding tools. It captures tool preferences, productivity gains, security concerns, and company policy alignment, giving engineering leaders a data-driven baseline for tooling decisions and workforce planning.

Run the survey when evaluating a new AI tool purchase, after a major platform release like a new Copilot or Cursor version, or during annual developer experience reviews. It is also timely when your organization is drafting or updating its AI usage policy, ensuring the policy reflects actual developer behavior rather than assumptions.

Cross-reference the Time-Saving Tasks and Weekly Time Saved fields to identify which workflows — boilerplate generation, debugging, or test writing — deliver the highest return. Then compare those gains by experience level and programming language to target training resources and tool licenses where they will have the most measurable impact on team output.

Segment security concern responses by company policy stance to reveal whether developers who work under a permissive policy report higher or lower risk perception than those under a restrictive one. Presenting this correlation helps security and engineering leadership calibrate policy strictness against actual developer sentiment rather than relying on generic industry benchmarks.

A developer experience survey covers the full engineering workflow — tooling, processes, team dynamics, and job satisfaction. An AI coding usage survey narrows the scope specifically to AI-assisted development: which models are used, which coding tasks benefit most, and where human expertise remains essential, making it the right instrument when AI adoption is the primary research question.