Developers Saving 10+ Hours Weekly with AI Tools Plummet Dramatically

The percentage of developers reporting they can save 10+ hours per week using AI tools has dropped significantly from 68% the previous year to 26%. This finding from Atlassian's "State of Developer Experience 2026" reveals a gap between expectations for AI and the reality experienced in practice.

Atlassian is a company that provides project management tools and developer software and regularly surveys the work experience of developers. Over the past few years, as generative AI began rapidly spreading into development environments, the expectation that "AI dramatically increases productivity" has spread throughout the industry. This survey is noteworthy for quantitatively demonstrating the gap between such expectations and reality.

According to the survey, only 28% of developers report that AI adoption has visibly reduced work stress and hassle compared to before. In other words, over 70% of developers do not perceive major changes in workplace friction—the cumbersome and inefficient aspects of their work—even when using AI. Meanwhile, reports also indicate that engineering leaders (managerial layers of development teams) spend more time reviewing and correcting AI-generated outputs than average developers.

This result suggests that developers are still in an intermediate stage of "mastering" AI tools. If AI-generated code and proposals cannot be used as-is and new work emerges to verify and correct outputs, the burden naturally becomes heavier for managers. A clear temperature difference is emerging between the benefits experienced by developers on the front lines and the burdens felt by those in organizational management positions.

Additionally, the sharp decline in perceived time savings from the previous year to this year may reflect growing variance in both proficiency with AI tools and methods of utilization. In the early adoption phase, a subset of users who actively experiment with AI tend to experience significant benefits. However, as tools become widely distributed in the workplace and more diverse developers begin using them, average satisfaction tends to decline. This shift is a predictable pattern.

This survey result again raises questions about the simplistic view of AI as "deploying it will increase productivity." For AI tools to truly create value in practice, post-deployment efforts become critical—including tool selection, designing usage methods, and providing team-wide training. The increased burden on engineering leaders signals that organizations have yet to optimize their AI utilization framework, and this indicator deserves attention when considering the future direction of development organizations.