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Study shows AI tools slow down task completion

Recent research indicates developers using AI tools completed tasks 19% slower than without AI.

July 20, 2025 at 07:00 PM

AI Coding Tools Underperform in Field Study with Experienced Developers

Recent research reveals a surprising 19% increase in task completion time among developers using AI tools.

AI tools show unexpected challenges in software development study

A recent study challenges the belief that AI tools speed up software development. Researchers at METR found that experienced developers using AI-enhanced tools, like Claude 3.5, actually took 19% longer to complete tasks compared to those who did not use AI assistance. This randomized controlled trial involved sixteen professional developers and examined their productivity over realistic tasks drawn from mature open-source projects. Participants were either given access to AI tools or were restricted from using them. The results contradict the widespread assumption that AI would significantly increase productivity, instead showing that AI can introduce subtle delays that cumulatively slow output, identified by researchers as a 'perception gap.'

Key Takeaways

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AI tools can slow task completion, not speed it up.

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A significant 19% increase in task duration was found.

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Developers expected a productivity boost but received a delay.

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The study emphasizes the need for rigorous evaluation of AI tools.

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Friction from AI interactions can go unnoticed but affects output.

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Future improvements in AI integration may enhance productivity.

"AI-assisted developers took 19% longer to complete tasks than those without AI."

This statement reveals the core finding of the study, highlighting the need for cautious adoption of AI tools in development.

"The perception gap illustrates a disconnect between expected and actual productivity outcomes."

This quote emphasizes the central theme of the study regarding AI's performance.

"Future improvements in AI integration may unlock real productivity gains."

This optimistic remark from the authors reflects their belief in potential advancements despite current challenges.

This study highlights a critical turning point in AI tool adoption within software development. While AI tools are often marketed as solutions to enhance speed and efficiency, the findings underline the importance of empirical evaluation in assessing their real-world utility. Developers' assumptions about productivity boost clash starkly with measurable results. The research calls for greater scrutiny of tool impacts rather than relying solely on developer perceptions, suggesting a need for better integration strategies that mitigate friction and truly enhance productivity.

Highlights

AI tools may promise speed but deliver delays instead.
The gap between AI optimism and reality is wider than expected.
Increasing productivity with AI requires a hard look at real impacts.
Friction in AI usage can be subtle but substantial.

Concerns about AI productivity and integration

The research shows that AI tools can introduce delays in software development, countering expectations of increased efficiency. This finding raises concerns for developers and companies relying on AI for productivity.

As developers navigate integrating AI into their workflows, real-world evaluations will remain crucial.

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software ai developers productivity research technology development research

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