A CEO who has AI on the agenda usually hears two kinds of messages. One comes from the teams running pilots and reporting successes. The other comes from the numbers, which show that little of that success flows through to the rest of the organization. Between those two messages sits a question the CEO eventually asks himself: is this down to the technology, to the people, or to something we haven't set up yet.
The question is rarely "does AI work here". That question has long been answered internally, usually with an example that did work. The question that remains is why that example doesn't work everywhere, and whether that is a scaling problem or a foundational problem. A CEO wants to know whether the organization as a whole is ready to carry AI, not whether one isolated team can work smartly with it.
That is a different kind of question than the ones asked by specialists in the organization. The COO looks at processes, the CIO at infrastructure, the CHRO at people and roles. For each of those angles there is a separate answer, found at what a COO looks at in AI maturity, what a CIO looks at in AI maturity and what a CHRO looks at in AI maturity. The CEO needs those answers, but his own question sits one level higher: are those three foundations in proportion to each other, or is the organization tilting because one is far ahead of another.
The risk for a CEO is not that AI fails. The risk is that the organization invests in the wrong order: money and attention going to applications while organization, IT infrastructure and data management are not yet at the level needed to carry those applications. Those are the foundational dimensions. They come before the dependent dimensions, not because that is a preference, but because that is the order in which it works. An organization with no view of that keeps running pilots that don't add up to anything larger, and pays for it in time, in the credibility of the program, and in the trust of the people who worked on it.
What he also stands to lose is the ability to explain to his supervisory board or shareholders where the organization stands. "We're doing AI" is not an answer a CEO wants to give when asked what it delivers. He needs something he can show: a level, a structure, a reason why the same question won't come back next quarter.
A CEO does not accept an answer that rests on a single perspective. If only IT says things are going well, or only HR says the people are ready, he knows that picture is colored by where it comes from. What he needs is a picture in which those perspectives sit side by side, with the differences visible instead of explained away.
He also does not accept an answer that lumps everything together. "AI maturity: 3 out of 5" tells him nothing if he doesn't know which dimension is pulling that number down and which is pulling it up. Without that breakdown he cannot set priorities, and every conversation about AI stays a conversation about feeling rather than about structure.
The maturity measurement from hybridresourcing is built on those two points. It looks at seven dimensions, from organization and IT infrastructure to data management and the dimensions that follow from those, and places each dimension at one of five levels: baseline, foundation, activation, insight, intelligence. That level is never the same across the whole organization. A company can be at foundation on data management and at activation on organization, and that very difference is what a CEO can act on.
The measurement works with a plotting round: several people from the organization score separately, without seeing each other's answers. The spread that results is itself information. If the CIO and the CHRO are far apart on the same component, that tells you something about how the organization views it, regardless of what the "real" level is. For a CEO standing between two conflicting messages, that spread is often more informative than the average.
This measurement says nothing about which tasks AI can take over or how much capacity that frees up. It measures whether the organization can carry it, not what there is to carry. Anyone who has that first picture and wants to know what the second one yields ends up at a different question: which part of the work can be taken over, and under what conditions. That is exactly what the work scan from FTE TO AI was built for. It calculates, per task, what share of the work can be taken over by AI, based on the nature of the task itself, not on the readiness of the organization behind it. The two measurements belong together in that order: first see whether the ground can bear the weight, only then calculate what can be built on it.
The tool with which organizations can go through this themselves is under construction. Anyone who wants to use the measurement as soon as it becomes available can sign up for the waiting list. For comparison: how an entire sector is dealing with this is described in how the construction sector scores on AI maturity.
Vraag maar wat er moet staan voordat AI in uw organisatie kan landen.
Answers come from this site’s knowledge base. Not tailored advice, and not a scan of your company.