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Create conditions. Don't optimise.
The most widespread leadership assumption under AI pressure goes: we need to make people faster, better, more adaptable. Dr. Gerald Hüther explains why this approach produces the opposite effect, and what leadership means instead.
There is a sentence in the work of Dr. Gerald Hüther that accompanies my work more than almost any other: it is not made. It emerges.
At first glance that sounds like a philosophical statement. It is a neurobiological one. And it contradicts what most organisations today understand by leadership, especially when pressure builds.
The logic of optimisation and why it fails
When companies introduce AI, they very often rely on a particular logic: people need to adapt, so training programmes are developed, processes are defined, expectations are communicated. Those who follow along are recognised. Those who hesitate are supported, sometimes pushed. All of this happens with good intentions, and yet it very often produces the opposite of what is intended.
Hüther describes this mechanism precisely: as soon as people experience being turned into objects of expectations, evaluations and measures, the brain withdraws. It shifts into protection mode. And in protection mode, learning is not possible, because the brain is using all available energy to secure itself rather than to develop. Optimisation creates exactly the conditions under which change becomes least likely.
What works instead
Potentialentfaltung, as Hüther describes it, starts from a different premise: in every person and in every team something is already present that can show itself and develop under the right conditions. The task of leadership is not to extract or force this potential. It is to create the conditions under which it can emerge.
That sounds passive. It is not. Shaping the right conditions is an active, demanding leadership task. It requires looking carefully at what a team actually needs right now. Safety? Clarity? The space to ask a question without being evaluated? The experience that one's own contribution matters, even when it is not yet perfect? These are not soft factors. They are the neurobiological prerequisite for a person being able to risk something new at all.
What this means for AI projects
I have accompanied AI implementations where everything worked technically and almost nothing worked on the human level. And I have seen teams that developed remarkable things with modest tools, because the conditions were right. Because someone had asked before explaining. Because mistakes were not punished. Because the direction was clear without every step being prescribed.
Leadership under AI pressure, as I understand it, does not mean bringing people to change. It means creating conditions under which change becomes possible. That is a fundamental difference that shows up in every meeting, every decision and every response to resistance. Whoever has internalised it leads differently. With more calm, more precision and more effect.
