85% of AI projects fail to reach production. Most failures are predictable—and preventable—with proper upfront assessment. This framework helps data leaders evaluate AI readiness before committing resources to initiatives that won't deliver value.
The AI Readiness Pyramid
AI success requires capabilities at each level. Skip a level and your project will fail:
Assessment Framework: 5 Dimensions
Dimension 1: Data Readiness
| Criteria | Not Ready (1) | Developing (2) | Ready (3) |
|---|---|---|---|
| Data Quality | No quality monitoring; known issues | Basic validation; some gaps | Automated quality checks; SLAs met |
| Volume | <10K training examples | 10K-100K examples | >100K examples with diversity |
| Labeling | No labeled data exists | Some labeled; inconsistent | Systematic labeling process |
| Accessibility | Data in silos; manual exports | Centralized but restricted | Self-serve access with governance |
Use Case Prioritization Matrix
Sample Readiness Scorecard
Assessment Outcomes
3x
Higher Success Rate
With proper assessment
$500K
Avg Savings
Avoided failed projects
6 mo
Faster to Value
Right-sized scope
Get Your AI Readiness Score
DataVerge offers complimentary AI readiness assessments for enterprises. We evaluate your data, infrastructure, team, and use cases to provide a prioritized roadmap for AI success.