The AI context gap: Enterprise AI organizations have a trust problem, not a retrieval problem — and most are still building the fix

Across 101 enterprises, the infrastructure that feeds AI agents their business context is being built faster than it can be trusted. Retrieval-augmented generation is already the default context source, and provider-native retrieval has quietly overtaken the dedicated vector databases that define the category — yet a majority of enterprises have already watched their agents produce confident, wrong answers traced to missing or inconsistent context. A governed semantic layer is emerging as the fi

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ethics.ai (16 July 2026), “The AI context gap: Enterprise AI organizations have a trust problem, not a retrieval problem — and most are still building the fix,” evidence record 11009, https://ethics.ai/record/11009 (originally published by VentureBeat).

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