The AI Data Economy in 2027: Five Predictions for Business Owners

1. Agent workflow data becomes a distinct category

Established: AI developers are building agents that complete multi-step tasks in software.

Forecast: records of how skilled people complete real workflows will be licensed as their own data type, with dedicated formats and pricing.

2. Private evaluation sets gain value

Established: public benchmarks are widely known and can leak into training data.

Forecast: unpublished, outcome-verified test sets from real businesses will be in higher demand, even in small volumes.

3. Physical-world and robotics data grows

Established: robotics and physical AI need sensor, video and operational data that is rarely online.

Forecast: logistics, manufacturing and field-service records will attract more licensing interest.

4. Vertical datasets beat generic volume

Established: reported per-unit prices for large generic archives can be low, such as the 2 to 4 cents per image Freepik reported.

Forecast: smaller, domain-specific collections in law, finance, healthcare operations and engineering will command more attention than bulk generic content.

5. Rights and provenance standards tighten

Established: publishers and platforms increasingly license content rather than leave it open, and EU and UK data protection rules already apply.

Forecast: buyers will expect documented provenance, consent records and clear licence terms as standard, making well-documented sellers easier to work with.

What to do now

Inventory what you hold, document where it came from and resolve rights questions early. Those steps are useful whichever way the market moves.