Companies that prioritize semantics in their AI-ready data will improve agentic AI accuracy by up to 80% and cut costs by up to 60% by 2027, according to new research released at the recent Gartner’s Data & Analytics Summit in London. “Agentic AI outcomes depend on context, including semantic representations of data,” Rita Sallam, distinguished VP analyst at Gartner, said at the summit. “Without context—a clear understanding of the specific relationships and rules within an organization’s data—AI agents cannot operate accurately.”The implication for CFOs: a meaningful share of today’s agentic AI spend is at risk of being wasted on tools that hallucinate, introduce bias, and produce unreliable outputs—not because the models are flawed, but because the underlying data lacks context.

Full report : Gartner argues the problem isn’t the models finance chiefs are buying—it’s the data context underneath.