An operating partner comes in with a different clock than management. There is a period in which value must grow, and AI is on the list of levers that can do that. The problem is that the list is usually drawn up by people who have an interest in a positive story. Management wants to show that it is looking ahead. A pilot with a chatbot or a dashboard with AI in the name goes over well in a quarterly update. The question the operating partner asks is a different one: is there something here that will still work in two years, or is this a demo that survives until the next steering committee.
What is at stake is not just a technology choice. It is the assumption behind part of the value creation. If an investment memo counts on efficiency gains from AI, and those gains turn out to rest on systems that do not serve two departments consistently, that is a risk that should have surfaced earlier. Conversely: a company that is quiet about AI but has its foundation in order may be able to move faster than the show-cases suggest. The operating partner who looks only at the pilots misses that difference in both directions.
The question is not "do you use AI". Everyone uses something by now. The question is whether the organization can carry AI in a way that holds up outside the test setup. That calls for the dimensions that rarely appear in a pitch: is the data an application runs on the same data the finance team uses for the figures that go to the board, or is it a separate export that nobody maintains. Is the infrastructure set up in such a way that an application can scale to a next location, or is it custom-built around the preferences of one IT manager who might leave after the exit. Is there a decision-making structure that takes responsibility for what a model outputs, or does that responsibility rest nowhere, becoming a liability question later.
These questions lie close to what a CIO asks about AI maturity and what a COO examines in the operational layer, but the operating partner asks them with a time horizon in mind. Not: is this good. But: is this sustainable until the next round, and is it transferable to a buyer who will run its own due diligence.
What he does not accept is an answer that rests on belief. "The team is enthusiastic" is not maturity. "We have an AI strategy on paper" is not maturity if nobody can point to which data flow feeds that strategy. And a score filled in only by the CEO or the CFO is an opinion with a number attached, not a measurement. If management, operational leadership and the person responsible for IT have three different pictures of how far the company has come, that spread is itself the signal — more important than the average.
That is why a score from one person carries insufficient evidentiary weight for an operating partner. A plot round in which several people score separately, and where the outcome is not one number but a distribution across five levels and seven dimensions, shows where the company stands on paper and where actual agreement stops. For an investment decision, that is a different kind of information than a report grade: it shows whether the foundation — organization, infrastructure, data management — is already in place, or whether it still needs to be built under a company that is already running AI applications standing on sand.
For an operating partner looking across multiple companies in a portfolio, comparability is just as important as depth. A sector like construction has different bottlenecks than the installation industry, and it is useful to know how construction on average stands with AI maturity or how the installation industry compares against the same five levels, before treating a portfolio company as an exception or as an example. Without that context, a score is an isolated number. With that context, it becomes visible whether a company is lagging behind its sector, or in fact ahead while the rest of the sector is still catching up.
This measurement is not about which work AI can take over. It is about whether the organization is ready for something to take over — whether the data, the infrastructure and the decision-making have reached a level that can bear what is placed on top of it. That is a different question from what tasks in a portfolio company are concretely replaceable, and that question is answered by the work scan from FTE TO AI, which calculates per task what portion of the work can be taken over by AI. Anyone who, as an operating partner, first wants to know whether the foundation under a company is solid enough to carry that outcome, starts here.
The maturity measurement from hybridresourcing.com is under construction. Anyone who wants to use the plot round for a portfolio company or for a series of companies can sign up for the waiting list. There is currently no dashboard and no report to download — but there is the option to get first access as soon as the instrument becomes available.
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.