Contingent and retained are fee models.
For AI seats they are incentive systems.
Contingent rewards list pressure.
Retained bonds to mandate and yes.
Christian Pobbig and Beyond Chiefs work from Hamburg on AI Executive Search in DACH. This page cuts the fee model for AI. It does not steal a retained-hub H1 and invents no fee percentages.
Pay follows close.
Pressure on volume and speed.
Research stacks when the seat is unclear.
For scarce AI bearers with a yes-cut, that is often misaligned.
Bond before the market.
Seat brief first. Then search.
Judgment outranks stacking.
No automatic win — but the right logic for a seat that is not interchangeable.
No fee percentages.
No ranking that “retained is always more expensive.”
No clone of the retained-method hub H1.
Only the cut: which incentive fits the AI yes.
Is the seat scarce and contested?
Do you need a cut before the longlist?
Does your model reward inflation — or judgment?
The answer drives the fee model — not the other way around.
Fee model follows seat risk.
A scarce yes does not tolerate a list incentive.
If the AI seat is real, open the AI Executive Search mandate retained to the yes.
If you mean contingent for volume roles, buy a different product.
No. Often wrong for scarce AI seats with a yes-cut.
No. Payment without a mandate is not judgment.
No. Incentive cut — no invented %.
