DORA 2025: 90% of Developers Now Use AI in Daily Work

Google's DORA 2025 report reveals a striking number: 90% of software development professionals now use AI in their workflows โ a 14% increase from the previous year.
Massive Adoption, Uneven Trust
The survey of nearly 5,000 tech professionals globally shows AI has become a familiar part of the developer toolbox. On average, each person spends 2 hours daily working with AI tools.
65% of participants report heavy reliance on AI for software development. Among them, 37% rate their reliance as "moderate", 20% as "a lot", and 8% as "a great deal."
However, the report also uncovers a notable "trust paradox." Only 24% of participants trust AI at "a lot" or "a great deal" levels. Conversely, 30% say they trust it "a little" or "not at all." This means AI is being used as a supporting tool, rather than a full replacement for human judgment.
Impact on Productivity and Quality
Positive findings from the report:
- 80% of participants say AI has boosted their productivity
- 59% report a positive impact on code quality
One important point: this year, AI adoption is directly linked to higher software delivery throughput โ a reversal from last year's findings. However, the challenge remains: ensuring software works as intended before reaching users.
AI as "Mirror and Multiplier"
The research reveals that AI functions as a "mirror and multiplier." In cohesive organizations, AI boosts efficiency. In fragmented ones, it exposes weaknesses.
The report also classifies 7 distinct team archetypes, from "Harmonious high-achievers" to teams stuck in "Legacy bottleneck." This classification helps organizations better understand the relationship between performance, employee satisfaction, and work environment.
Blueprint for Organizations Adopting AI
Google proposes 7 core capabilities to maximize AI's impact:
- Clear workflows โ AI works best when processes are already standardized
- Continuous learning culture โ encourage experimentation and accept failures
- Effective measurement โ track specific metrics, not just gut feelings
- Security and governance โ build frameworks for AI risk management
- People training โ invest in AI skills across the entire team
- Workflow integration โ use AI as a core component, not an add-on
- Leadership support โ commitment from management is the deciding factor
What This Means for Developers
The 90% figure doesn't mean every developer needs to use AI immediately. But it shows the trend is clear. Developers should:
- Understand how AI tools work, including their limitations
- Evaluate whether AI truly fits their specific type of work
- Maintain core skills โ AI is a supporting tool, not a replacement for technical thinking
The DORA 2025 report confirms one thing: AI has shifted from "experimental" to "standard." The question is no longer "should I use AI?" but "how do I use AI effectively?"
Related Posts
Is AI Deskilling Programmers? A Frontend Developer's Perspective
A 252-point Hacker News article asks: is AI repeating the 'lost decade' of frontend development? A deep dive into deskilling, leaky abstractions, and how developers can adapt.
Simple Programming Languages and AI Coding Agents
AI coding agents perform better with less fragmented ecosystems. Go, Rails, and Rust produce more stable output than JavaScript or Python โ reshaping how developers choose their stack.
Context Engineering: The New Skill More Important Than Prompt Engineering in 2026
Prompt engineering isn't dead, but in 2026 the real differentiator is context engineering โ how you structure information so AI coding agents can work effectively on your project.