Connecting AI agents to enterprise knowledge
For all the data that AI systems continually amass and analyze, enterprise AI agents often suffer from a curious shortcoming: a lack of knowledge.
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Key points
- More than data, knowledge is the understanding of what the data means in the context of individual organizations.
- AI agents need this understanding to reason about situations, make decisions, and ultimately take actions.
- A lack of knowledge, our research finds, is a major reason agentic AI use cases never make it to production.
- First, it seeks to gauge organizations’ agentic knowledge capabilities (i.e., their ability to give AI agents a full contextual understanding of the data they ingest) across semantic knowledge, episodic memory, and procedural knowledge.
Sources (1)
- [1]Connecting AI agents to enterprise knowledgeMIT Technology Review (AI) · Oct 5, 03:47 PM
For all the data that AI systems continually amass and analyze, enterprise AI agents often suffer from a curious shortcoming: a lack of knowledge.
More than data, knowledge is the understanding of what the data means in the context of individual organizations.
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Before this
- Oct 5, 2026Sharing AI progress in mathematics
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