Skip to main content
Lornets

Evidence note

State of AI-assisted Software Development 2025

Industry Research2025DORA / Google Cloud

What was examined?

DORA's 2025 research programme examining AI adoption and its relationship with individual development work and software-delivery systems.

Key findings

  1. 01AI adoption among technology professionals was high.
  2. 02Most respondents reported perceived productivity benefits.
  3. 03DORA characterises AI primarily as an amplifier of the engineering system surrounding it.
  4. 04Higher AI adoption was associated with greater delivery throughput while also being associated with greater instability in the 2025 analysis.

Why it matters. Lornets interpretation.

AI can accelerate local development activity without automatically improving every downstream production outcome. Testing, delivery, platform capability and operational feedback remain part of the performance of the overall system.

This is the Lornets reading of the source, not a finding of the source itself.

What it does not establish

  1. 01DORA's organisation-level findings are primarily associative and should not automatically be interpreted as causal.
  2. 02The results do not establish that AI inherently reduces software stability.
  3. 03The effect of AI depends on organisational and technical context.

Source

Organisation
DORA / Google Cloud
Evidence type
Industry Research
Published
2025
Status
Current

Read the original research

Relevant Lornets framework areas

Framework domains

  • Delivery & Change Control
  • Observability & Operations
  • Architecture & Maintainability

Related evidence

Source record

Published
2025
Last verified
2026-08-11
Source status
Current
Back to Research & EvidenceRead the Production Assurance Methodology