The five readiness axes, one by one

AI readiness is easy to declare. For each axis below, we compare what leaders say with what the same survey finds, and propose the question a committee should ask. All of it is self-reported. Each pair comes from different questions, so read the contradiction without subtracting one number from the other.

In the Drexel and Precisely survey, 88% of leaders say they have data ready for AI. In the same survey, 43% name data as their biggest obstacle. Precisely sells data integrity, and the study itself attributes shifts between editions to a change of sample.

The committee should ask: for the first use case, which data is missing today, and who answers for it?

Deloitte asked US leaders to rate their preparedness for AI agents across seven areas. Strategy came first, with 52% saying they are prepared. Business processes came last, with 21%. The cut: US only, and only those already piloting agents. Deloitte sells consulting.

The committee should ask: in this process, which step changes or goes away, and who decides?

In IBM’s survey, 86% of CEOs believe employees have the skills to use AI. The same CEOs estimate that 25% of the workforce uses AI regularly. These are CEO opinions and estimates, with no measurement of use, and IBM sells AI and consulting.

The committee should ask: who uses it, how often and in which function, and where does that figure come from?

In Gartner’s survey, 71% expect to use AI agents within 12 months, and 21% say they have the capacity to govern them. The first number is the respondents’ own expectation. Gartner sells advisory services.

The committee should ask: who can stop a system in production, under what rule, and where is that written?

The Drexel survey shows the same pattern: 87% say they have the infrastructure they need, and 42% name it as their biggest obstacle. The same limits apply.

The committee should ask: what does it cost to run this in production, and who tracks that cost?

Cisco’s index breaks Brazil down by pillar. The most prepared group, scoring 86 or more, fell from 29% in 2023 to 18% in 2025. In 2025 that group was 16% in data, 26% in talent, 18% in governance and 18% in infrastructure. Worldwide, the total went from 14% to 13%, which is stable. The limits matter: Cisco sells infrastructure, doesn’t publish n by country, and a jump in the 2025 data suggests a change of instrument we could not check.

Brazil’s statistics agency, IBGE, offers an official figure on people. In industry, among companies with 100 people or more, 54.2% of those that adopted advanced digital technologies cite a lack of qualified staff. Among those that did not adopt, a small group, it is 60.6%. The figure covers digital technologies in general, and the statistic is experimental.

Companies that call themselves more ready consistently report better results. That is association. We found no study that follows a readiness score over time and tests whether it anticipates financial return. A score is useful for ranking gaps, and it gives no basis for promising a return. No number here is a Nebuloz result.