AI in software development is expanding beyond code completion into AI coding assistants, agentic tools and wider development workflows. SlashData’s AI in software development research examines how developers adopt these technologies, which tasks they use them for and where perceived productivity gains differ from everyday reliance. Explore developer survey findings, adoption data and benchmarks covering generative AI, code generation, AI-assisted workflows and developer productivity. The research brings evidence to questions about how AI tools are used and how developer behaviour changes over time.
88% of professional developers work with AI models, tools, APIs, or services.
Code generation is the most common task developers report using AI for, with almost half (49%) of those using AI assistants doing so for this purpose.
34% of developers using AI developer tools in agentic modes say difficulty estimating cost before a task runs limits how much autonomy they give AI agents. As vendors move to metered pricing, predictable cost becomes part of the product.
62% of developers with 16+ years of experience say AI developer tools cut the time they spend on repetitive tasks, against 42% of developers with 0-2 years. SlashData's Developer Nation Q1 2026 data from 4,203 professional developers shows the return on AI rises with experience.
79% of developers building AI features use open models, but only 51% reach production, against 63% for closed models. SlashData and Mozilla surveyed 1,494 developers in May 2026.
