Data Tiles
AI Readiness Framework

What makes a data product AI-ready?

AI systems need more than access to data. They need trusted, governed, explainable and fit-for-purpose data products. The Data Tiles AI Readiness Framework defines the eight dimensions and 37 measurable metrics used to assess whether a data product is ready for decisions, analytics and AI.

View the 37 MetricsAssess Your AI Readiness
Section 1

The Eight Dimensions of an AI-Ready Data Product.

Every AI-ready data product is measured across these eight dimensions. Together they describe what "trusted enough for AI" actually means in practice.

Dimension 01
Completeness & Quality
Measures whether the data product is accurate, complete, current and fit for its intended decision or AI use case.
Dimension 02
Semantic Clarity
Ensures business meaning, terms, definitions and relationships are explicit, not assumed.
Dimension 03
Feature Readiness
Confirms the data product is structured and usable for analytics, AI models and agentic workflows.
Dimension 04
Observability & Stability
Tracks freshness, reliability, drift, failures and operational health over time.
Dimension 05
Governance & Policy Enforcement
Applies access, privacy, usage and compliance policies at the point of creation and consumption.
Dimension 06
Lineage & Explainability
Makes provenance, transformations, dependencies and decision logic traceable and explainable.
Dimension 07
Interoperability
Ensures the data product can be consumed across BI, AI, data platforms and enterprise workflows.
Dimension 08
Trust & Usage Signals
Shows whether people and systems are using, trusting and reusing the data product.
Section 2 · #metrics

The 37 Metrics that make AI readiness measurable.

Beneath each of the eight dimensions sits a set of operational metrics. Together they turn AI readiness from a slogan into a measurable, continuous property of every data product.

Dimension 01
Completeness & Quality
5 metrics
  • Completeness %
  • Null Rate on Model-Driving Features
  • Outlier Rate / Anomaly Frequency
  • Consistency Across Sources
  • Label Quality Score
Dimension 02
Semantic Clarity
4 metrics
  • Business Term Coverage
  • Field Description Completeness
  • Join Path Clarity Score
  • Ambiguity Score
Dimension 03
Feature Readiness
5 metrics
  • Feature Availability Score
  • Feature Freshness
  • Historical Depth
  • Granularity Alignment Score
  • Derived Feature Coverage
Dimension 04
Observability & Stability
5 metrics
  • Schema Drift Frequency
  • Data Drift Score
  • Pipeline Reliability
  • Data Freshness SLA Compliance
  • Variance in Key Metrics Over Time
Dimension 05
Governance & Policy Enforcement
5 metrics
  • Policy Coverage
  • Policy Enforcement Success Rate
  • Sensitive Data Classification Coverage
  • Access Auditability Score
  • Compliance Alignment
Dimension 06
Lineage & Explainability
4 metrics
  • End-to-End Lineage Completeness
  • Transformation Transparency Score
  • Reproducibility Score
  • Source Traceability Score
Dimension 07
Interoperability
4 metrics
  • API Accessibility Score
  • Query Success Rate via Natural Language
  • Latency for AI Query Execution
  • Tool Integration Readiness
Dimension 08
Trust & Usage Signals
5 metrics
  • Trust Score
  • Adoption Rate
  • Query Success vs Failure Rate
  • AI Usage Frequency
  • Decision Impact Score
From framework to software

From framework to working data products.

Data Tiles owns the AI Readiness Framework. Latttice operationalises it in software by helping teams create, govern, measure and share trusted data products that are ready for decisions, analytics and AI.

Create

Turn business intent into structured, reusable data products.

Govern

Apply policy, access, lineage and stewardship at the point of creation and consumption.

Measure

Track readiness signals so AI readiness becomes a continuous property of every data product.

Ready to assess whether your data products are AI-ready?

Start the AI Readiness AssessmentSee Latttice in Action