Digital maturity was long measured by presence: a customer portal, automated invoicing, a dashboard for the customer. Whoever had that led the conversation. The comparison was about investments made, not about what those investments delivered. A supplier with three systems won the conversation over a supplier with one system, regardless of what happened with the data from those systems.
That criterion is shifting. Not because digitalization is becoming less important, but because the question is changing from "do you have it" to "what does it do without a human touching it". A customer portal that only shows a status is different from a portal that flags a deviation, proposes a cause, and prepares a solution for approval. The first is digitalization. The second is digital maturity as it counts now.
Behind every claim about digital maturity sits a stack of operational work that used to be human work: gathering data from various systems, recognizing patterns, flagging deviations, formulating an initial proposal, and presenting that proposal to someone who approves or rejects it. At most companies, part of those steps still runs through people who compile reports and forward them manually. At a growing number of companies, AI does the flagging and proposing, and an employee only assesses the end result.
That difference does not lie in ambition but in what happens under the hood. A company with clean, connected data can hand a task over to AI that at a company with scattered spreadsheets is still entirely human work, even if both companies are labeled "digitally mature" on paper. So the comparison is no longer about the number of systems, but about how much of the work behind them runs by itself and how much oversight it still requires.
A customer notices digital maturity not in the interface but in the speed and initiative of the response. Does he get a notification before he has to call himself, or only when he asks? Is a deviation in delivery explained with a concrete cause, or with a generic apology that follows three days later? Is the report he receives an export from a system, or an interpretation that already takes into account what is relevant to him?
These differences are measurable in turnaround time, in the number of times a customer has to seek contact himself, and in how often a notification contains a correct diagnosis without human post-processing. They are not measurable by the number of digital tools a supplier mentions on its website.
Whether a company gains an edge here depends on three things: the quality and integration of the underlying data, the willingness to actually let an AI proposal serve as an endpoint rather than as a supplement to an existing process, and the extent to which oversight is set up as reasoned assessment rather than as repetition of the work. Companies that have these three in order see digital maturity shift from a cost item to a demonstrable difference in the conversation with the customer. Companies where the data is still scattered keep digitalizing without the pace of customer contact noticeably changing.
This is not a matter of budget alone. Two companies with comparable IT investments can differ widely here, simply because one has cleaned up its underlying processes and the other has not. Such a difference is hard to detect in a conversation, but can be demonstrated.
The shift does not only affect digital maturity as a standalone theme. It is connected to how easy it is to do business as a customer, as elaborated in what automation of customer processes changes about ease of doing business, to the extent to which geographic spread is still a handicap when systems but not people are present everywhere, as discussed in how AI shifts the meaning of geographic coverage, and to the question of whether certifications still prove the same thing now that part of the underlying checks runs automatically, as explained in what certification still demonstrates when AI does part of the checking.
The underlying question — which work at this specific company can genuinely be taken over by AI — differs per organization and is answered per task with the work scan from FTE TO AI.
This does not touch on personnel decisions; what an employer does with that outcome falls under its own legal requirements, which are not addressed here.
The claim "we are digitally mature" is just as easy for a competitor to make as it is for you. The difference emerges in what is demonstrable underneath it: which step is automated, which still runs with oversight, and which remains entirely human work. Anyone who does not know how competitors come by proof without published figures will find an approach in how to obtain information about competitors who do not publish figures, and anyone who notices that all claims in the sector sound interchangeable can read why that is the case in why competitors all sound the same in their promises.
The free dimension check shows what that means for your own position: you state where you think you win, and see which of those claims can be defended with evidence. The full benchmark, with the peer group on all dimensions side by side, is under construction.