AI and Developers in 2025: Insights from Google’s Revealing Report

Google has recently released its annual DevOps Research and Assessment (DORA) report, which seeks to understand how development teams are adopting artificial intelligence and to identify the practices, capabilities, and organizational conditions that impact their performance. The report uses a mixed-methodology approach, combining nearly 5,000 responses from a global survey of software professionals with statistical analysis and qualitative interviews. Here’s an overview.

Ambivalent but Massive Adoption of AI

The widespread adoption of AI by developers is undeniable, and this trend did not slow down over the past year: 90% of respondents report using AI in their work by 2025, marking a 14.1% increase from 2024. Additionally, this usage is far from occasional: over half of the respondents spend 2 hours or more per day on AI tools. This seems to be becoming a habit: 6 out of 10 respondents turn to artificial intelligence when facing a problem, and 7% indicate that this approach is systematic.

The majority of respondents are satisfied with the contributions of AI: 80% believe it enhances productivity, while 59% feel it positively impacts the quality of their code.

AI Enhances Strengths and Exposes Weaknesses

“The research reveals a fundamental truth: the primary role of AI in software development is that of an amplifier. It amplifies the strengths of highly effective organizations and the dysfunctions of those struggling,” Google states in the preface of its report. To support this idea, the study outlines 7 archetypes of development teams:

1. Foundational challenges: teams in survival mode, high instability, and burnout.
2. Legacy bottleneck: outdated and restrictive systems, morale and performance suffering.
3. Constrained by process: heavy procedures, stability without efficiency.
4. High impact, low cadence: valuable outcomes, but rare and unstable deliveries.
5. Stable and methodical: reliable and enduring work, albeit at a slower pace.
6. Pragmatic performers: quick cadence and stability, with room for engagement improvement.
7. Harmonious high-achievers: a rare balance between performance, stability, and well-being.

These clusters illustrate that the impact of AI is not uniform: it strengthens healthy practices in high-performing environments and exacerbates issues in fragile contexts. More concretely, the report indicates that AI increases the pace of delivery but also increases the instability of deployments. According to Google, only about 40% of respondents, specifically those in archetypes 6 and 7 (Pragmatic Performers and Harmonious High-Achievers), are fully leveraging AI tools.

Effective Adoption Strategies for AI

For the first time, Google delves deeper in its report by offering recommendations for the implementation of AI tools. Here are the 7 tips provided by Google for AI to have positive effects rather than causing chaos:

1. Clear AI Policy: the report emphasizes that an organization must define explicit rules to govern the use of artificial intelligence. These rules clarify team responsibilities and set acceptable boundaries.
2. Healthy Data Ecosystem: Google advises companies to ensure the quality, reliability, and accessibility of their data. This strategy prevents information silos and ensures data consistency.
3. Quality Internal Platform: according to the report, an organization should develop a robust technical infrastructure to support its teams. This platform should be treated as an internal product and subject to continuous improvement.
4. User-Centric Approach: the document states that a team should focus on the needs of developers and clients when making decisions. The tangible impact of AI on experience and value creation is consistently evaluated.
5. Working in Small Batches: the report suggests breaking tasks into smaller segments to reduce risks associated with automation. By favoring short cycles and frequent deliveries, teams enhance the efficiency and resilience of projects that incorporate AI.
6. Version Control and Continuous Integration: Google reminds that a team must apply rigorous standards to govern software production. AI-generated code is subjected to thorough testing and strict monitoring.
7. Culture of Experimentation and Learning: the report stresses the importance of fostering quick feedback loops and technical curiosity. This approach particularly values initiatives.