In many companies, commerce runs through one person: the owner, the account manager from day one, the one who knows which client expects which tone and which price is still acceptable. That knowledge is nowhere on paper. It lives in conversations, in negotiations, in sensing a connection that either forms or doesn't. For day-to-day operations, that works well. For a buyer, it's a risk that gets priced in.
The dependency did not arise from unwillingness. It is the result of speed: someone who is good with contact gets more clients, more responsibility, more relationships tied to their name. No one ever decided it should work this way. It grew, and only becomes visible at the moment a sale is on the table.
A buyer asks a simple question: what keeps running if this person is out for three months. If the answer is "little," that gets reflected in the price, usually in the form of a longer transition period, a portion of payment contingent on client retention, or a lower multiple. Client concentration plays directly into this: how that is weighed is described on what client concentration means for a company's valuation. Commercial knowledge tied to one person and revenue tied to a few clients often reinforce each other: the same person usually also holds the most important clients.
Commercial work consists of several layers, and not every layer is equally transferable. Part of it is administrative: who spoke with whom and when, which agreements were made, which pricing tier applies to which client. That part AI can already capture and make searchable today, without needing someone who knows it by heart.
Another part is pattern recognition: which client responds to which approach, where the signs point to a client about to leave, which seasonal pattern explains a dip. This is work where AI can surface signals, but where someone still assesses whether the signal is correct and what to do with it. Oversight with reason, not automatic action.
The third part is the relationship itself: the conversation in which a client feels heard, the negotiation in which a feel for the other party determines the outcome. That remains human work. AI can improve the preparation for it, not replace the conversation.
Whether a company can already make use of this shift depends on whether the commercial information was ever recorded. Companies where CRM use is mandatory and conversations are logged can now have that layer structured and made searchable. Companies where everything sits in one person's head first need something to structure before AI can do anything with it.
The risk of transfer is not only that knowledge disappears, but also that a client feels shifted from a fixed point of contact to a system. Making it transferable does not mean the contact changes before the client notices. It means that the information currently held by only one person also becomes readable elsewhere: which agreements are running, which preferences apply, where the sensitivities lie. A second person can then follow along and, at some point, take over, without the client experiencing the handover as a loss.
That process often also touches the contract side: long-term agreements promised to a person but never put on paper weigh differently to a buyer than agreements on paper. Which contract form makes a buyer more at ease is described on which contract terms a buyer considers value-preserving. And because commercial dependency often coincides with who makes the decisions, the comparable question for decision-making can be found on how decisions that currently rest with one person can also be made without that person, and for the network behind the deals on how a salesperson's personal network becomes part of the company instead of part of the person.
Which tasks within your own commercial function AI can already take over today, which can be done under oversight, and which remain human work differs per company. That breakdown by task is exactly what the FTE TO AI work scan answers.
This topic touches on personnel, and what an employer does with this in terms of tasks, roles, or agreements falls under its own legal requirements; this page only describes where the dependency lies and what can be structured around it.
The free value check consists of eight short questions, one per value driver, and gives a picture of which driver is weighing most heavily on your price today. For many companies, that is owner dependency, with commercial knowledge as its largest component. The full value scan, with a maturity score per driver and a two-year calendar toward the exit moment, is under development.