A buyer does not pay for the profit that is stated, but for the profit that can plausibly be shown to persist without the current owner, without the current people and without the current suppliers. That is profit quality: not the size of the margin, but its origin. Now that AI applications are taking over parts of the work, that origin is visibly shifting. A saving that arises because a task is structurally carried out faster or cheaper carries different weight than a saving that results from one cheap supplier, one temporary rate agreement or one person who happens to do a lot of work for little salary.
The question a buyer asks is simple: if I take over this company, will this margin remain intact? Profit quality is therefore not about the size of the profit, but about the stability and repeatability of the sources from which that profit originates. If part of the margin comes from work that is now largely done by a system, with human oversight that approves or rejects, that is a different source than a margin that rests on an individual negotiation with a supplier that can simply be revised after the takeover. How these two sources relate to one another changes the valuation of the profit as a whole.
In practice, a buyer looks at how the cost structure has built up over recent years. Did a cost saving arise from a one-off action, or is it the result of a process that has been adjusted and that keeps that adjustment? At companies where AI takes over part of the administrative processing, planning or first-line customer contact, a buyer sees this reflected in structurally lower hours per unit of work, not in an exceptional year. At companies where that change has not yet been implemented, the margin remains dependent on the people who do the work today and on the terms agreed with them or with suppliers. That difference between companies does not lie in the sector, but in the extent to which work has already been redistributed between what a system takes over, what happens under oversight and what remains human work.
Within the value scan, profit quality is assessed on the basis of how the margin has built up over multiple years, the spread of cost items across suppliers and processes, and the extent to which savings have been embedded in a way of working rather than in an individual agreement. It is examined whether a saving can be traced back to a task that is fully done by a system, to a task that runs under oversight, or to a task that is still entirely human work and therefore remains sensitive to absence, departure or negotiation. That breakdown produces a maturity score with the evidence that goes with it: not an estimate, but a traceable substantiation.
Profit quality improves when a saving shifts from a person or a supplier to a process. That means that work still done with human oversight today is carried out demonstrably and repeatably, with a documented reason for approval or rejection, instead of with an individual judgment that is not documented. It also means that a saving tied to a single supplier is broadened or laid down in a contract with a longer term, so that it does not disappear as soon as the owner leaves. Which tasks lend themselves to this and which do not is a factual question about the work itself, not about the people who carry it out; where this subject touches on decisions about personnel, its own statutory requirements apply, separate from this assessment.
Profit quality is closely linked to other value drivers. A margin that depends on the owner personally has a different risk profile, as described in what owner dependency does to a sale price now that AI takes over tasks, and a margin resting on a small number of customers is by definition less stable, as set out in how customer concentration affects a company's value in a sale. The extent to which revenue is fixed in advance also plays a role here, see what recurring revenue is worth in a sale, and anyone who wants to work through the substantiation themselves will find the steps in how you substantiate profit quality with your own figures.
Whether a saving sits in the process or hangs on one person or supplier is ultimately a question of which work in this company can genuinely be taken over by AI, and that question is answered task by task with the work scan from FTE TO AI.
The free value check consists of eight short questions, one per value driver, and gives a picture of which driver is putting the most pressure on your price today. The full value scan, with maturity scores, evidence per driver and a two-year calendar toward the exit moment, is under construction.