CFOs Could Cut Agentic AI Costs Up to 60% by Fixing This Overlooked Data Problem

In the race to deploy AI agents, many companies are overlooking a costly problem hiding in plain sight: data without context.

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.

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.

“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.”

Gartner argues that traditional schema-based data models are no longer sufficient, and that a dedicated semantic, or “context,” layer needs to sit at the core of enterprise data infrastructure. Skipping it, Sallam warned, will “perpetuate data inefficiencies” and expose companies to heightened financial, legal, and reputational costs.

For CFOs, the takeaway reframes the AI conversation from a technology debate into a capital-allocation one. Semantic coherence, Gartner says, is becoming “a cost-control and trust strategy, not a nice-to-have,” and potentially a focus for regulators and audit committees evaluating how AI-generated outputs flow into financial reporting and disclosures.

AI remains high on the executive agenda, as data from Q1 earnings calls shows. John Butters, VP and senior earnings analyst at FactSet, recently shared an analysis of S&P 500 earnings calls with me. At least 65% of S&P 500 earnings calls have cited the term “AI” so far, which Butters said slightly below the previous quarter’s 68%. But that prior quarter was the highest percentage going back at least five years, he noted, which makes the current 65% the second-highest share of S&P 500 earnings calls citing “AI” over that period.

When it comes to AI agents, semantics is no longer just semantics. It’s becoming a non-negotiable foundation. Will CFOs need to become linguists, too? Probably not. But they already wear plenty of hats — and the one labeled “chief context officer” may be next on the rack.

 

This article was written by Sheryl Estrada from Fortune and was legally licensed through the DiveMarketplace by Industry Dive. Please direct all licensing questions to legal@industrydive.com.