User Guidelines

Comprehensive guide to the Gartner AI Maturity Assessment Framework

Framework Overview

Understanding the Gartner AI Maturity Assessment structure

7
Dimensions
25
Capabilities
81
Sub-Capabilities

Maturity Levels

The 5 levels of AI maturity progression

LevelNameDescriptionCharacteristics
Level 1Initial / Ad-HocNo formal AI strategy. Isolated experiments with limited impact.
  • No governance
  • Manual processes
  • Siloed data
Level 2DevelopingBasic AI initiatives underway. Some processes defined.
  • Basic governance
  • Pilot projects
  • Some documentation
Level 3DefinedStandardized processes. Organization-wide AI strategy in place.
  • Clear standards
  • Trained teams
  • Measured outcomes
Level 4ManagedQuantitatively managed AI operations. Continuous improvement.
  • KPI-driven
  • Automated monitoring
  • Proactive management
Level 5OptimizingAI-driven innovation. Leading industry practices.
  • Industry leader
  • Continuous innovation
  • Strategic AI integration

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Outdated Evidence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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