AI in software development is changing how developers write, test, review and maintain code. Our guides and analysis explain AI coding assistants, agentic workflows, adoption challenges and the gap between using an AI tool and relying on it for real work. Follow AI software development trends through clear takeaways from developer surveys, tool-focused explainers and commentary on changing workflows. Looking for adoption figures, underlying data or independent benchmarks? Explore our AI in software development research.
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.
You don’t need another AI hype post, so I will keep the intro part short and sweet. 2 AI software developer insights you need to know in Q2 2026: AI in developers’ workflow & the ROI measurement gap.
SlashData Q1 2026 insights on AI adoption among developers, AI ROI measurement, and how software teams evaluate the value of AI developer tools.
66% of game developers use AI. See what 2,000+ devs think about speed, creativity, jobs, and player experience.
Agentic AI is transforming work—but also expanding attack surfaces. Learn how to harness autonomous AI agents securely, with guardrails, governance and logs.
Agentic AI has left the lab. SlashData’s Q3 2025 study of 12,000 developers shows ChatGPT (64%) and GitHub Copilot (49%) leading, half of adopters already shipping agentic AI to production, while privacy and quality concerns still slow broader GenAI rollout.
Artificial intelligence is transforming how software is built, deployed, and maintained. Yet, questions persist: Are AI-assisted tools really improving software delivery performance
This is the transcript of our latest live session “Artificial Intelligence in Tech: usage, adoption and challenges in 2025” which you can watch in the following video.
Explore how different developer profiles, experience levels, and company sizes are shaping the adoption of generative AI. A must-read for product, programme, and analyst teams.
This article focuses on how technology managers approach security and risk management in AI.
