Field Note

Are you sure your data is AI ready? Data Foundations to Drive AI-Enabled Enterprise Value

AI and ML only monetize data that is accurate, complete, consistent, current, traceable, and legally usable. The dimensions to assess it by.

Oleg Simonov

4 Oct 2026

2 min read

Enterprise data is frequently claimed as an intangible asset in investment theses, yet AI and ML only monetize data that is accurate, complete, consistent, current, traceable, and legally usable. Another common mistake is valuing the volume or exclusivity of data before establishing its usefulness for a specific AI application. A dataset may be syntactically clean yet measure the wrong outcome, omit the population that matters, contain future information or lack the rights needed for deployment.

If you need to establish your platform data quality, assess it along the following 27 dimensions across 9 categories:

Preparation Phase

Foundational Quality	Structural and Temporal Quality	Coverage and Distribution Changes	Provenance Rights and Documentation
- Completeness - Accuracy and Correctness - Label Quality	- Consistency - Validity and Conformity - Uniqueness and Deduplication - Timeliness and Freshness	- Representativeness - Coverage and Balance - Distribution Stability and Drift - Evaluation Integrity and Fairness - Bias and Fairness - Volume and Data Sufficiency	- Provenance Lineage and Reproducibility - Privacy Compliance and Permitted Use - Documentation

Operationalization Phase

Generative Training Corpus Quality	Retrieval and Answer Quality	Adversarial and Historical Integrity	Multimodal and Synthetic Data	Controls for Operational AI Agents
- Corpus Filtering - Benchmark Decontamination - Mixture Balance	- RAG Retrieval and Generation Quality - Parsing and Extraction Fidelity	- Data Poisoning and Adversarial Integrity - Point in Time Correctness - Source Authority and Conflict Resolution	- Multimodal Alignment - Synthetic Data Quality	- Authorization and Tenant Isolation - State and Tool Integrity - Deletion and Revocation Propagation - Feedback and Outcome Coverage

Thank you for reading. Are you dealing with or thinking about this topic? Whether it’s AI spending without a P&L story, a margin that won’t move, or a diligence process ahead, I’d like to hear thoughts!

— Oleg

Tell me what you’re working on

See how I work with companies

— Oleg

Tell me what you’re working on

See how I work with companies