AI Maturity Assessment
A 5-level organizational readiness model for understanding where you are and what’s next on your AI journey.
Not every organization is ready for the same level of AI investment. The AI Maturity Assessment provides a 5-level model for understanding where your organization stands and what’s needed to advance.
The Five Levels
Level 1: Awareness
The organization recognizes AI’s potential but has no active projects. Leadership is curious but uncommitted. No dedicated budget or team exists.
- Key indicator: AI discussions happen in strategy meetings but not in sprint planning
- Next step: Identify one concrete business problem where AI could help
Level 2: Experimentation
Small teams are running pilots. Individual developers use AI coding tools. There’s no organization-wide strategy, but pockets of innovation exist.
- Key indicator: Some teams use AI tools; others don’t know about them
- Next step: Document wins and share across teams
Level 3: Integration
AI is part of the development workflow. Teams have guidelines for AI usage. There’s a budget and some dedicated resources. Results are being measured.
- Key indicator: AI usage policies exist and are followed
- Next step: Build shared infrastructure and centralize learnings
Level 4: Optimization
AI is driving measurable business outcomes. The organization has dedicated AI teams or roles. Processes are optimized around AI capabilities. ROI is tracked and positive.
- Key indicator: AI initiatives have clear metrics tied to business goals
- Next step: Scale what works; sunset what doesn’t
Level 5: Transformation
AI is a core competitive advantage. Business strategy is informed by AI capabilities. The organization builds proprietary AI solutions. Culture embraces continuous AI adoption.
- Key indicator: Competitors can’t easily replicate your AI-driven advantages
- Next step: Invest in moats — proprietary data, unique models, specialized talent
Assessment Guidelines
To assess your organization honestly:
- Survey engineering leads on current AI usage (not aspiration)
- Audit AI spending vs. measurable outcomes
- Check if AI initiatives survive leadership changes
- Ask: “If we turned off all AI today, what breaks?”
Most organizations overestimate their level by 1-2 stages. The gap between experimentation and integration is where most get stuck.
Where does your organization honestly sit? The answer determines what AI investments make sense today.