Data valuation
How business data is valued for AI.
Quick answer
Data valuation for AI estimates what a dataset is worth to buyers who will use it to train or evaluate models. Value depends on task relevance, scarcity, quality, volume, recency, rights and exclusivity, minus the cost of preparation and privacy work. There is no public price index; actual value is established through buyer demand and negotiation.
Approaches
- Market approach: comparison to similar deals (limited because few are public)
- Income approach: expected licensing revenue over time
- Cost approach: cost to recreate the data
- Utility approach: measured improvement to a model
Deal structures that affect value
- One-time vs recurring delivery
- Exclusive vs non-exclusive
- Per-record, flat fee or revenue-linked
Limits
Online estimates, including SourceX's estimator, are illustrative ranges, not offers.
Related
- SourceX Enterprise Data Value Framework (/data-value-index)
- How do AI companies value datasets? (/questions/how-do-ai-companies-value-datasets)
- How AI data deals are priced (/insights/how-ai-data-deals-are-priced)
Related resources
- IndustryBPO & contact centers data
- IndustryRecruiting & staffing data
- SolutionHow AI developers source data
- QuestionHow do AI companies value datasets?
- QuestionShould companies sell or license their data?
- InsightHow much is my company data worth to AI companies?
- SolutionData partnerships between businesses and AI developers
- InsightIs it safe to license company data for AI training?
- InsightHow is company data anonymized before AI training?
- DataWorkflow data
- DataSales and CRM data
- GlossaryDataset
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