User Guidelines
Comprehensive guide to the Gartner AI Maturity Assessment Framework
Framework Overview
Understanding the Gartner AI Maturity Assessment structure
Maturity Levels
The 5 levels of AI maturity progression
| Level | Name | Description | Characteristics |
|---|---|---|---|
| Level 1 | Initial / Ad-Hoc | No formal AI strategy. Isolated experiments with limited impact. |
|
| Level 2 | Developing | Basic AI initiatives underway. Some processes defined. |
|
| Level 3 | Defined | Standardized processes. Organization-wide AI strategy in place. |
|
| Level 4 | Managed | Quantitatively managed AI operations. Continuous improvement. |
|
| Level 5 | Optimizing | AI-driven innovation. Leading industry practices. |
|
Scoring Methodology
How maturity scores are calculated and validated
How to Qualify for Level 3+
Key requirements to achieve "Defined" maturity and beyond
Common Pitfalls to Avoid
Mistakes that often lead to lower scores or failed assessments
Insufficient Documentation
Relying on verbal claims without written policies or procedures.
Outdated Evidence
Submitting documents from previous years that may not reflect current practices.
Missing Implementation Proof
Having policies on paper but no evidence of actual implementation.
Inconsistent Responses
Different team members providing conflicting information about the same capability.
Overestimating Maturity
Claiming higher levels without evidence to support the assessment.
Ignoring Governance
Focusing only on technical capabilities while neglecting governance and ethics.
Best Practices for Success
Tips to maximize your assessment score and demonstrate true maturity
Prepare Comprehensive Evidence
Gather multiple types of evidence (documents, screenshots, metrics) for each capability.
Cross-Reference Documentation
Ensure policies reference implementation guides and both align with actual practices.
Involve Multiple Stakeholders
Include perspectives from IT, business, legal, and executive teams.
Be Honest About Gaps
Accurately assess current state to create realistic improvement roadmaps.
Document Everything
Maintain audit trails, meeting minutes, and decision logs for AI initiatives.
Track Progress Over Time
Use assessment cycles to demonstrate continuous improvement.
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