Structured data lives in databases and spreadsheets with defined fields and consistent formats — transaction records, CRM entries, sensor readings. Unstructured data is everything else: emails, PDFs, contracts, support tickets, call transcripts.
Unstructured data contains enormous amounts of valuable business information — but it requires AI to extract structured meaning from it before it can be acted on at scale. A bank whose structured data is loan account records in a core banking system and whose unstructured data is the supporting documents submitted with each application is using AI extraction to bridge the two — turning documents into data that the core system can use.
