About this Report

Generative AI has entered the developer toolkit, but how deeply has it actually embedded itself into the work? This report examines how developers are using AI across their workflows: which tasks they are turning to AI for, how much of each task they are willing to hand over, and where the gap between adoption and reliance reveals the limits of current tooling.

Drawing on survey data from developers actively using AI-assisted software development tools, the findings move beyond headline adoption figures to examine the texture of AI use across more than a dozen distinct development tasks. The result is a more honest picture of where AI is genuinely accelerating developer work, where it has found a willing audience for tasks developers are happy to offload, and where capability gaps are suppressing the trust needed for deeper reliance.

For organisations evaluating or expanding AI tool adoption, the data offers a practical lens for calibrating expectations, informing governance, and identifying where human oversight remains essential. For those building the next generation of AI developer tools, it maps the frontier clearly: the tasks with high demand and low trust are not side thoughts; they should be the roadmap.