Report: The AI Productivity Paradox

Full Report: What data from 10,000 developers reveals about impact, barriers, and the path forward. Insights from our analysis of 1,255 teams across leading software engineering organizations.

Desk showing the Operationalizing AI in Software Engineering report next to coffee and glasses

Report: The AI Productivity Paradox

Full Report: What data from 10,000 developers reveals about impact, barriers, and the path forward. Insights from our analysis of 1,255 teams across leading software engineering organizations.

Desk showing the Operationalizing AI in Software Engineering report next to coffee and glasses
Chapters
Faros Research

Faros Research

Faros Research studies how engineering teams build, deliver, and improve. From annual reports to customer insights, our analysis helps enterprises understand what's working (and what's not) in AI-native software engineering.

AI Is Everywhere. Impact Isn’t.
75% of engineers use AI tools—yet most organizations see no measurable performance gains.

Read the report to uncover what’s holding teams back—and how to fix it fast.
Cover of Faros AI report titled "The AI Productivity Paradox" on AI coding assistants and developer productivity.
Discover the Engineering Productivity Handbook
How to build a high-impact program that drives real results.

What to measure and why it matters.

And the 5 critical practices that turn data into impact.
Cover of "The Engineering Productivity Handbook" featuring white arrows on a red background, symbolizing growth and improvement.
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An industrial technology leader lays the foundation for AI transformation with Faros

Learn how a global industrial technology leader used Faros to unify 40,000 engineers and build the measurement foundation for AI transformation.

Customers
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A leader in independent identity verification measures AI impact with Faros

Learn how a leading identity security provider uses Faros to power an AI-driven engineering organization and achieve a 35% increase in velocity.

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Monorepo vs Polyrepo: What the PR benchmark data actually shows

Benchmark data from 320 teams comparing monorepo and polyrepo PR cycle times. What “good” looks like and why developer infrastructure matters, especially for AI agents.