AI Adoption
Learn about AI adoption patterns for your team
Track how your team is adopting AI coding assistants and visualize usage patterns across different tools, team members, and time periods.
AI adoption doesn't happen uniformly—it varies by individual preference, seniority, delivery pressure, and organizational enablement efforts. Our research shows that simply purchasing AI tools doesn't guarantee adoption. Successful rollouts require deliberate enablement, peer learning, and creating space for experimentation outside of high-pressure delivery cycles.
Daily Active Users (DAUs)
What it is:
Daily Active Users (DAU) measures the percentage of your team actively using AI coding assistants each day. When viewing weekly charts, we show the average of daily percentages across that week.
Why it matters:
DAU helps you understand adoption momentum and identify patterns over time. A high DAU indicates that AI tools have become part of your team's daily workflow. Sharp increases often follow enablement sessions or peer learning initiatives, while dips during high-pressure periods (like before a product launch) may indicate that developers don't have time to learn a new tool, or don't see the value of AI in making them faster.
How we calculate it:
For each group (team, level, geography, tool), we calculate the percentage of people who used AI tools that day. In most views, we count anyone who used ANY AI tool. In the AI Tool view, we calculate DAU separately for each specific tool—so if someone uses both Cursor and Claude Code on the same day, they count towards the DAU for both tools.
What good looks like
In our research, we found that teams with strong AI adoption typically see 50%+ DAU among their high AI users. Note that DAU is just the starting point for whether AI could be having an impact in your organization; you'll need to combine this with AI Impact Measurement to understand outcomes. Look for sustained usage over time rather than initial spikes that fade.
Super-users
What it is
Super-users are team members who demonstrate consistently high AI tool usage. These individuals have often developed effective workflows and practices that work well on your specific codebase.
Why it matters
Super-users are a great source of learning and insights on how to get more from AI tooling.
Super-users are usually high AI users because they enjoy learning the latest AI practices, and they’ve already learned what works best on your organization’s codebase. (For example, AI still struggles with complex code-bases – but your AI super-users may have developed unique ways to get around this.)
Our research shows these users have great principles for using AI well – and that others really want to learn from their peers, so super-users are a great place to start with your peer-to-peer learning initiatives.
How we identify super-users
We identify super-users based on two factors; usage intensity and consistency. The specific metrics vary by tool (actual spend for Claude Code and our AI integration API, and "expected spend" for Cursor), but the principle remains the same across all tools.
Selection Criteria: Super-users are identified per tool and must meet both requirements:
Top 10% usage on that specific tool
Consistency filter: Regular activity over the measurement period
This dual-criteria approach ensures we identify users who are both heavily engaged and consistently using AI tools, rather than those with occasional spikes in usage.
How to use information on super-users
Identify and interview your super-users to understand their workflows
Document specific prompts and practices that work on your codebase
Create peer-to-peer learning opportunities where super-users demonstrate real examples
Scale proven practices in playbooks and standards (e.g., in shared rules or markdown files that you recommend people put into LLM memory)
Developers trust their peers more than external hype – and sometimes even more than they trust leaders. Showing how AI works on your actual codebase, shared by team members they respect, is one of the most effective things you can do to accelerate adoption.
Last updated
Was this helpful?