A deeper look at AI's impact through the SPACE framework
A short while ago, I posted about different frameworks for measuring developer productivity, including the holistic SPACE framework. I recently came across an article from Research-Driven Engineering Leadership that provides a great real-world application of this model: RDEL #104: How does the SPACE framework apply to AI’s impact on engineering?.
The article summarises a detailed study that surveyed over 500 developers to understand how AI tools are changing their work. The findings confirm what many of us might suspect, but it is valuable to see it backed by data.
Key findings from the research
The study shows that AI adoption is widespread, with 75% of developers reporting regular use. For those who use AI, the benefits are clear across most dimensions of the SPACE framework:
- Activity & Efficiency: 88% of users reported improved task throughput, and 82% felt their efficiency had increased.
- Performance: 71% believe AI helps them deliver more customer or business value.
- Satisfaction: 62% reported higher job satisfaction since using AI tools.
The research highlights that AI excels at handling repetitive work, freeing up developers to focus on more complex challenges. As some participants noted in the full paper:
“It takes care of so much tedious work!” “I’m still stuck solving all the hard problems”
The nuance of collaboration
A more nuanced story emerges around the Collaboration dimension. Fewer than half of the developers (48%) agreed that AI improved their ability to collaborate, with a significant portion remaining neutral.
However, the qualitative interviews in the study revealed that AI is not hindering collaboration but changing its nature. Developers are less likely to interrupt colleagues with simple coding questions, as they can turn to an AI assistant first. This reduces low-value interruptions and shifts team conversations towards higher-value topics like architecture and brainstorming.
The critical role of team culture
The research also underscores a critical factor that goes beyond the tool itself: team and organisational culture. Developers in organisations that actively support AI adoption are seven times more likely to use it daily.
This reinforces a key point from the research paper: when AI adoption is high within a team, individuals perceive greater benefits for both the team and themselves.
“Developers on teams with higher AI adoption don’t just rate their team as more productive—they also report stronger personal agreement that AI makes themselves more productive.”
This suggests that shared learning, best practices, and a supportive environment are essential for maximising the benefits of AI. It is not just about providing a tool, but about a culture where it can be used effectively. This study provides valuable evidence for why a multi-dimensional framework like SPACE is necessary to understand the true impact of a technology like AI.
