Research-based assessment of the human side of AI adoption — skills, habits, and culture, validated across 44 teams.
Teams Tested
Maturity Levels
Survey Types
“We thought our engineering team was ahead on AI. The index showed Culture was the real bottleneck, not skills. We’d never have found that without the data. Two teams were already at Level 4, the rest were sitting at Level 2. That single view changed where we put the training budget this quarter.”
Co-Founder & CTO, Ralabs
“We thought our engineering team was ahead on AI. The index showed Culture was the real bottleneck, not skills. We’d never have found that without the data. Two teams were already at Level 4, the rest were sitting at Level 2. That single view changed where we put the training budget this quarter.”
Co-Founder & CTO, Ralabs
“We thought our engineering team was ahead on AI. The index showed Culture was the real bottleneck, not skills. We’d never have found that without the data. Two teams were already at Level 4, the rest were sitting at Level 2. That single view changed where we put the training budget this quarter.”
Co-Founder & CTO, Ralabs
“We thought our engineering team was ahead on AI. The index showed Culture was the real bottleneck, not skills. We’d never have found that without the data. Two teams were already at Level 4, the rest were sitting at Level 2. That single view changed where we put the training budget this quarter.”
Co-Founder & CTO, Ralabs
“We thought our engineering team was ahead on AI. The index showed Culture was the real bottleneck, not skills. We’d never have found that without the data. Two teams were already at Level 4, the rest were sitting at Level 2. That single view changed where we put the training budget this quarter.”
Co-Founder & CTO, Ralabs
DevWorld conference, netherlands
Harvard Business Review
WAW Tech conference, WARSAW
AI investment keeps growing. Clarity on what’s actually happening with people doesn’t. Here’s what AI Adoption Score makes visible.
Maps every person, team, and department to one of 5 maturity levels across Skills, Usage, Culture, Impact, Vision, and Governance.
The AI Knowledge Sharing dimension surfaces where knowledge is siloed — and the best practice library helps teams close the gap.
AI Individual Skills Distribution maps each person’s expertise so you can allocate training by actual gap, not assumption.
One week to know exactly where your organization stands on AI
Each survey targets a different dimension of AI adoption. Use them individually or combine them into a full picture.
Ralabs’ full methodology — combines all dimensions below into a single comprehensive score across every role in your organization.
10 questions. A fast self-check to understand where you stand compared to the current market — designed as an entry point into deeper assessment.
Identifies what your employees are actually afraid of when it comes to AI — so you can address the real blockers, not the assumed ones.
Maps each person’s specific AI expertise — who knows which tools, who builds automations, who follows the latest models.
Maps how your team generally relates to AI in the workplace — from skepticism to enthusiasm — before you invest in training or tools.
Measures your team’s belief in AI as a long-term force — both trust in current tools and confidence in an AI-shaped future.
Reveals whether a culture of sharing AI knowledge actually exists in your organization — or whether people keep their workflows to themselves.
Uncovers the real reasons your team isn’t using AI more effectively — whether that’s access, confidence, habits, or something else entirely.
Identifies AI archetypes across your team — visionaries, practitioners, skeptics — so you can build balanced teams where every perspective is represented.
One week. A clear picture of your organization’s AI performance — and exactly what to do next.
