AI Maturity Assessment Scorecard: From Manual to Autonomous
A practical maturity framework for deciding what to automate now, next, and later.
AI Maturity Assessment Scorecard: From Manual to Autonomous
You cannot plan AI rollout well without a baseline. Maturity scoring creates that baseline and prevents over-scoping.
Four practical maturity levels
- Level 1 Manual: mostly ad hoc execution
- Level 2 Assisted: isolated AI usage, low standardization
- Level 3 Systemized: repeatable AI workflows and ownership
- Level 4 Autonomous: monitored automation with controlled escalation
Use the AI Maturity Assessment to place your team honestly.
Score across capability dimensions
Focus on:
- data quality and availability
- process definition
- model and prompt governance
- monitoring and review loops
One weak dimension can block the whole system.
Translate score into a 90-day plan
Each score band should map to clear action:
- low score: pick one pilot workflow
- mid score: standardize two workflows and reporting
- high score: expand automation with quality gates
Pair quick and deep assessments
Use AI Readiness Quiz as a lightweight entry point, then run full maturity scoring for roadmap decisions.
Convert maturity to resourcing decisions
After scoring, estimate effort with Project Cost Calculator. This keeps strategy tied to delivery reality.
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