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Preliminary data from a longitudinal AI impact study

newsletter.getdx.com

March 11, 2026

2 min read

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45/100

Summary

Preliminary data from a longitudinal AI impact study indicates that AI productivity gains are approximately 10%, rather than the previously suggested 10x. High expectations for AI productivity, influenced by social media and vendor marketing, may not align with these findings.

Key Takeaways

AI productivity gains in engineering are approximately 10%, significantly lower than the 2-3x increases often suggested by marketing.
During a study of 40 companies, AI usage increased by an average of 65%, but pull request throughput only rose by 9.97%.
Developers report that coding is not the primary bottleneck in their workflow, as planning and other human-centric tasks remain largely unchanged.
The ongoing study will further investigate why some teams achieve greater productivity gains with AI and how leaders can facilitate this.

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Community Sentiment

Mixed

Positives

A broad 10% productivity improvement across industry is significant, indicating that AI's impact could be transformative, even if it doesn't seem headline-worthy.
LLMs have effectively reduced the cost of deployment, allowing for quicker iterations and potentially reshaping how coding is approached in the future.
The rapid iteration capabilities of AI tools are enabling programming teams to work much more efficiently, suggesting a shift in productivity dynamics.

Concerns

The marginal effect on PR throughput raises concerns about the actual productivity gains from AI, suggesting that the improvements may not be as impactful as anticipated.
Relying on PR throughput as a metric for AI productivity is flawed, as it does not capture the true potential of AI in transforming development processes.
Skepticism around the validity of AI productivity enhancements from 2024 data highlights the uncertainty and potential overestimation of AI's impact on developer roles.