Developers now using AI tools in their daily workflow.
Only a minority trust the output accuracy of AI tools.
Faster cycle times for high-AI usage on standard tasks.
Experienced developers are slower on complex tasks.
Report spending more time fixing AI-generated code that is "almost right, but not quite," creating a new maintenance burden.
Still rely on human colleagues when the code gets complicated and stakes are high, indicating AI's limits in critical contexts.
Adoption is high, but efficiency is situational. Success requires a bifurcated strategy: use AI to accelerate routine boilerplate, but maintain rigorous human oversight for complex architectural work.