The first State of AI-Assisted Software Development report has arrived and it's from the same team that brought us a decade of DevOps research. The new report is based on almost 5,000 responses from technology professionals worldwide and over 100 hours of interviews. The report delivers a crucial insight for technology leaders:
AI's primary role in software development is that of an amplifier. It magnifies the strengths of high-performing organizations and the dysfunctions of struggling ones.
"The greatest returns on AI investment come not from the tools themselves, but from a strategic focus on the underlying organizational system: the quality of the internal platform, the clarity of workflows, and the alignment of teams."
Transform your AI strategy with these 3 crucial takes
1. AI adoption has reached critical mass, but trust remains low
In case you didn't notice the momentum, the report confirms that 95% of technology professionals now use AI at work. This near-universal adoption represents a dramatic shift from just three years ago, when AI use in development was still surprising.
2. The DORA AI capabilities model
Perhaps the most actionable finding is DORA's new AI Capabilities Model, which identifies seven foundational practices that are proven to amplify the positive impact of AI on organizational performance:
- Clear and communicated AI stance: Organizations with explicit, well-socialized AI policies see amplified benefits in individual effectiveness and organizational performance
- Healthy data ecosystems: High-quality, accessible, and unified internal data sources significantly boost AI's impact
- AI-accessible internal data: To be useful, AI tools must be connected to internal systems so they can become more context-aware
- Strong version control practices: Frequent commits and robust rollback capabilities are essential because, you know, things go wrong
- Working in small batches: Breaking changes into manageable units amplifies AI's positive influence on product performance
- User-centric focus: Teams that prioritize end-user experience see amplified team performance from AI adoption
- Quality internal platforms: Well-designed platforms with standardized capabilities amplify AI's organizational performance benefits
Organizations that implement these capabilities experience fundamentally different outcomes from AI, while organizations lacking these foundations often find they only create localized pockets of productivity that are often lost to downstream chaos.
3. AI improves throughput but decreases stability
In a shift from 2024's findings, AI adoption shows a positive relationship with software delivery throughput, reversing last year's negative correlation. This suggests that teams, tools, and organizations have begun adapting to the AI paradigm.
The research also reveals a persistent challenge: AI adoption increases software delivery instability. Teams have learned to move faster with AI, but their underlying systems haven't yet evolved to manage AI-accelerated development safely.
Why this research matters for your organization
The DORA research provides critical evidence that successful AI adoption is fundamentally a systems problem, not a tools problem. Organizations rushing to adopt AI without addressing their foundational capabilities risk amplifying existing dysfunctions rather than achieving the transformational benefits they seek.
Join the DORA Community
The insights shared here represent just a fraction of the valuable findings in the full report. The complete report includes a detailed analysis of:
- Platform Engineering adoption (now at 90% of organizations)
- Value stream management as a force multiplier for AI
- The socio-cognitive impact of AI on developers
- Practical implementation guidance for each AI capability
- Comprehensive methodology and research model details
You can access the full report and join a community of practitioners working to improve software delivery performance. Join the conversation shaping the future of AI-assisted development.
