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title: The State of AI Impact in Engineering: Q2 2026 | daily.dev
description: DX's Q2 2026 report analyzing AI impact across 500+ engineering teams reveals that over 50% of code is now AI-generated (up from 34% in Q1), but the picture is...
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# The State of AI Impact in Engineering: Q2 2026

**[Engineering Enablement](https://daily.dev/sources/engineering_enablement)** · 4 min read · 5 upvotes · 1 comments

## Summary

DX's Q2 2026 report analyzing AI impact across 500+ engineering teams reveals that over 50% of code is now AI-generated (up from 34% in Q1), but the picture is mixed. While developers save 4–6 hours per week, the Developer Experience Index dropped, PR sizes nearly doubled, and change confidence declined 6.1% even as code maintainability improved. AI spend surged from ~$1.5K to ~$44K per quarter at the median, yet the innovation ratio remained flat — meaning saved time isn't converting into new feature work. Engineering leaders are urged to move beyond velocity metrics and focus on downstream ROI, quality, and resolving systemic bottlenecks.

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <https://newsletter.getdx.com/p/the-state-of-ai-impact-in-engineering>

## Questions this post answers

### What percentage of code is now generated by AI according to recent industry benchmarks?

Over 50% of code is now AI-generated, specifically 52% in Q2 2026, up sharply from 34% in Q1 2026. This rapid increase suggests that once AI coding tools are deployed, their output quickly propagates through codebases via reviews, dependencies, and shared workflows across teams.

_Engineers tracking how fast AI-generated code is spreading through codebases can follow the trend on daily.dev._

### Is AI coding assistance actually improving developer experience or making it worse?

The net effect is currently negative: the Developer Experience Index (DXI) dropped from 67 to 65 over four quarters despite AI improving documentation quality, code maintainability, and onboarding speed. The decline stems from new friction such as larger pull requests, slower reviews, and less incremental delivery, showing velocity gains alone don't capture the full picture.

_Teams weighing AI tool adoption against developer experience tradeoffs can track findings like these on daily.dev._

### Why has median pull request size nearly doubled since AI coding tools became widely adopted?

Median PR sizes have nearly doubled as AI adoption increased, because AI-assisted development generates far more code per change, which correlates with increased complexity, more potential bugs, and added friction during code review since reviewers must process more lines per PR.

_Developers rethinking review workflows as AI inflates PR size can follow this shift on daily.dev._

## Similar posts on daily.dev

- [AI in engineering: Q2 2026 benchmarks & research readout](https://daily.dev/posts/ai-in-engineering-q2-2026-benchmarks-research-readout-a5bsn2lal) · Engineering Enablement · 10 upvotes · 0 comments
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---

Tags: [#productivity](https://daily.dev/tags/productivity), [#ai-coding](https://daily.dev/tags/ai-coding), [#technical-debt](https://daily.dev/tags/technical-debt), [#dora-metrics](https://daily.dev/tags/dora-metrics)

[View this post on daily.dev](https://daily.dev/posts/the-state-of-ai-impact-in-engineering-q2-2026-ynv5kqw0q)

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