Gartner Says Lack of Semantics Causes Inaccurate AI Agents and Wasted Spending
Neglecting semantics will cause AI agents to be inaccurate and inefficient, exposing organizations to wasted spending and increased data and AI governance vulnerabilities, said Gartner, Inc., a business and technology insights company.
AI agents need to understand the context inputs in each step of the agentic workflow to deliver accurate responses at an optimal cost.
Speaking at the Gartner Data & Analytics Summit in London today, Rita Sallam, Distinguished VP Analyst at Gartner, said: “Agentic AI outcomes depend on context including semantic representations of data. Without context – a clear understanding of the specific relationships and rules within an organization’s data – AI agents cannot operate accurately and are far more likely to hallucinate, introduce bias and produce unreliable results.
“Organizations that fail to adopt comprehensive context structures — supported by a robust data layer — will perpetuate data inefficiencies and face heightened financial costs, as well as legal...
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