What AI can do with your unstructured data (and what you need to get it right)

Unstructured data, including documents, emails, media, transcripts, and operational records, lacks fixed schemas and is estimated to comprise roughly 90% of enterprise information, making it difficult for traditional databases and business intelligence systems to process. AI technologies such as natural language processing, computer vision, OCR, semantic search, and retrieval-augmented generation can interpret this content, extract structured fields, summarize records, and support tasks such as contract review, claims routing, and knowledge retrieval. However, fragmented repositories, unclear version histories, inconsistent permissions, and unclassified sensitive material can cause AI systems to retrieve outdated information or expose content improperly. Effective use of AI therefore depends on centralized content management, access controls, classification, versioning, retention policies, and human review for high-stakes decisions. The text presents Box’s tools, including Box AI, Hubs, Shield, Governance, Relay, Sign, and Extract, as services intended to combine AI-assisted content analysis and workflow automation with document-level security, governance, and collaboration controls.

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