Vague AI generates no value

Article by Nacata Security, 17/08/2026

Does your company claim to use AI but fails to show how or where?

A study reveals that this does nothing to drive growth.

Researchers from Carnegie Mellon University and Larridin analyzed 564 companies across 12 different sectors, cross-referencing thousands of financial data points, job postings, and regulatory disclosures.

The conclusion is surprising: it is not how much you invest in AI that drives growth, but how concretely you can explain what that AI actually does within your business.

The study measured something no one had measured before.

The researchers built a metric called «narrative concreteness»: how specific a company is when describing its AI systems in official disclosures. Saying «we use artificial intelligence to improve efficiency» is not enough. You must name the system, explain how it is deployed, and show measurable results. Companies that did this consistently appeared at the top of the revenue growth rankings.

Eight percentage points of difference. That is enormous.

Companies at the top end of that metric recorded annual growth 8.0 percentage points higher than those at the bottom end, after controlling for sector, size, and prior growth. This is not a minor statistical nuance: it is a real gap that separates those who have actually implemented AI from those who only talk about it in presentations and press releases.

Talking about AI without evidence does not move a single dollar more.

Larridin’s AI Transformation Tracker scored 562 companies from 1 to 5 on adoption, team competency, and real impact. Several broad metrics lost strength when adjusted for context. The one that withstood every control was the hardest to inflate: a concrete, verifiable description of what AI is doing today.

AI does not improve margins. Not yet.

The study found no improvements in operating margins or stock market profitability. AI expands capabilities and generates new revenue — it does not cut costs. That changes how you should evaluate whether a company is truly leveraging this technology.

There is one exception that breaks the mold.

Companies providing AI infrastructure told a completely different story. This group outperformed its peers by around 32 percentage points over four months. These are the companies selling the foundations on which everything else is built: chips, memory, processing. The study excluded five major semiconductor companies from its main analysis to prevent their extraordinary performance from skewing the overall results.

Job postings also tell their own story.

More than 30,000 job postings from 536 companies were classified to measure what proportion sought profiles oriented toward building or operating AI and machine learning systems. That indicator showed no significant association with revenue growth, although the hiring data was collected after the period analyzed.

The industrial sector is where concreteness matters most.

In industries with intensive physical assets, describing precisely how AI is used helps distinguish those who already have it operational from those still experimenting. Deploying AI in physical environments requires real changes to infrastructure and processes.

This does not prove causality. But it does point to something.

The researchers themselves are clear: the study does not prove that AI causes higher growth. Companies that are already growing well have more resources to implement and document it. But the statistical relationship between concrete descriptions and revenue growth withstood every control, making it a signal that is hard to ignore.

Concreteness is the new business credential.

If a company cannot tell you exactly which AI system it uses, where, and with what measurable results, it has probably not gotten anywhere yet.

Do you really know whether your company uses AI or just says it does?

Security is not improvised, it is audited. At Nacata Security we detect vulnerabilities and protect your company, because a single flaw can cost you everything you have built.

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