The AI Workforce Maturity Model
Assessing Your Progress from Initial Experimentation to Ecosystem Leadership
The Current AI Landscape
of enterprises are still in Stage 1: Experimenting with AI and building basic literacy.
milestones are used in models like CNA’s to create detailed, actionable roadmaps for government agencies.
Stages 3 (Scale) & 4 (Ecosystem) correlate with above-average financial performance, linking maturity to ROI.
What Stage Is Your AI Workforce In?
1
Experiment & Prepare
Focus on building AI literacy, formulating policies, and conducting small-scale experiments. Most organizations (28%) start here.
2
Industrialize
Simplify core processes and begin applying foundation models on secure platforms to streamline operations and build capabilities.
3
Scale
Integrate AI into enterprise-wide decision-making loops, automating processes without constant human oversight for major efficiency gains.
4
Ecosystem
Develop proprietary AI, create new AI-driven services, and become a leader that sells AI capabilities to others in your industry.
A Look at Leading AI Maturity Models
MITRE AI Maturity Model
5 Levels (Initial to Optimized)
Organization pillar, skills, and experiential adoption across all levels.
20-dimension multiple-choice tool with scores and visuals.
MIT CISR Enterprise Model
4 Stages (Experiment to Ecosystem)
AI literacy, skills-building, and integrating AI into decision loops.
Team self-assessment via surveys and interviews.
CNA Model (Gov-Focused)
Performed, Established, Optimized
Skills planning, recruitment, retention, and fostering emerging talent.
Self-assessment against 450+ detailed milestones.
