From the Handelsblatt archive: The higher the position, the greater the expectation of AI competence. A top headhunter reveals exclusively which questions he uses to check - and when he immediately sorts out applicants.
Human and AI skills: Managers should master both. Photo: Getty Images
Dusseldorf. Artificial intelligence (AI) and a lousy economy – companies are not only hiring fewer, they are also cutting jobs. It's no longer just clerks who are affected. Even managers are no longer safe from AI. According to the Federal Employment Agency, there were 14.3 percent more unemployed managers in 2025 than in the previous year.
Because AI can already take over parts of management tasks today: resource planning, calculation, cost control. The “Job-Futuromat” of the Institute for Labor Market and Occupational Research (IAB) calculated that 67 percent of the managerial job profile can be replaced by algorithms. Particularly at risk: middle management.
» Read also: AI can take over up to 67 percent of tasks: And suddenly managers are also replaceable
Anyone who wants to get to the top today has to prove themselves more than ever. This is exactly where headhunter Bernhard Stieger separates suitable candidates from those who can't make it further up the ladder. With a few questions, which he made available exclusively to the Handelsblatt.
How would you have answered his questions? And would you still have a chance of getting a management position?
“Artificial intelligence not only changes processes and business models – it also changes the requirements for leadership,” says Stieger from the HR consultancy Spencer Stuart, which recently filled the top position at Biontech, for example.
Bernhard Stieger: The headhunter attaches great importance to the use of AI. Photo: Spencer Stuart
That's why it's no longer enough in job interviews to ask about technological understanding or experience with individual AI applications, says Stieger. "True AI maturity cannot be recognized by whether a manager knows the latest tools or is particularly adept at prompting. What matters is whether they understand how AI changes value creation, enables better decisions and makes the organization future-proof."
Using a questionnaire, Stieger and his team regularly check whether someone simply claims to have AI competence or whether they actually have it. “We are looking for people who can rethink their business model, make better decisions and take responsibility – especially where AI reaches its limits,” says Stieger.
The questions were checked and assessed by Martina van Hettinga, co-head of the personnel consultancy I-Potentials. “The catalog is essentially correct: AI does not make judgment less important, it becomes a crucial leadership skill,” she says. In the end, a questionnaire can only ever be part of a much more detailed process (combination of interviews, case studies, references, assessments).
Van Hettinga advises applicants not to just invest in pure AI knowledge. Because “the more tasks that can be delegated to AI, the more emphasis is placed on what has always made the difference in leadership positions: leading.” So, for example, deciding on a direction and convincing others to go along with it.
And so Stieger also says: “The most convincing leaders are not characterized by detailed technical knowledge, but by strategic judgment, learning agility and the ability to responsibly translate technology into leadership and business.”
Individual answers to his questions would therefore never decide on a candidate. However, some of Spencer Stuart's answers would make them pay attention because they could indicate a lack of strategic thinking, poor judgment or a low willingness to change.
The questionnaire
What we pay attention to: whether the manager understands AI as a strategic lever and recognizes effects on the business model, customers, competition and value creation.
What convinces us: The manager describes specifically where AI creates new value – for example through new business models, personalized customer solutions, faster innovation or better decisions. It can explain why a competitive advantage will arise in the future.
What makes us skeptical is that the answer comes down to individual tools or efficiency gains. It is not clear how AI could sustainably change the business model or competitive position.
What we look for: the ability to reflect strategically, be open to disruption and be willing to question your own assumptions.
What convinces us: The manager recognizes, for example, that customers could have completely different expectations of speed, individualization or advice in the future, or that the current differentiation from competitors will fundamentally change as a result of AI. What is crucial is that she derives concrete consequences from this.
What makes us skeptical is when the existing business model is taken for granted. Or when your own assumptions or possible disruptions are hardly reflected.
Red Flag: Statements such as “Our business will hardly change as a result of AI” or “This affects other industries more” indicate a low strategic awareness of the problem.
What we pay attention to: whether AI has actually changed your own understanding of leadership and decision-making.
What convinces us: The manager describes, for example, how decisions are now made more based on data, more time is invested in strategic issues or routine activities are consciously delegated to AI.
What makes us skeptical: AI is described as a relevant topic without this being reflected in concrete decisions or in one's own leadership behavior.
What we pay attention to: strength of implementation, ownership and entrepreneurial thinking.
What convinces us: The manager describes a specific project - for example an AI-supported optimization in sales, production or customer service; their personal contribution and the business benefits achieved.
What makes us skeptical is that it primarily describes company or IT initiatives. What role the manager himself played remains unclear.
What we look for: judgment, critical thinking and a sense of responsibility.
What convinces us: The manager shows how she weighed data, experience, context and responsibility against each other and made an informed decision despite AI recommendations.
What makes us skeptical: AI is either fundamentally trusted or fundamentally rejected. A differentiated examination of opportunities and risks is not apparent.
Red Flag: Statements like “If the AI recommends that, it will be right” or “I would never trust an AI in principle” show a lack of judgment.
What we look for: Understanding of the limitations of AI as well as integrity and responsibility.
What convinces us: The manager mentions, for example, personnel decisions, strategic direction decisions or ethically sensitive issues and explains clearly why human judgment remains indispensable here.
What makes us skeptical: No clear boundaries are stated, or AI is fundamentally seen as a replacement for human decisions.
Red Flag: “If the data is correct, AI could take over every decision in the future.”
What we pay attention to: innovative ability, future thinking and change orientation.
What convinces us: The manager consistently rethinks processes, roles and collaboration and describes how this improves speed, quality or customer benefit.
What makes us skeptical: The answers are limited to minor optimizations. There is no evidence of a fundamentally new way of thinking about processes or business models.
What we pay attention to: prioritization, resource allocation and economic thinking.
What convinces us: Investments focus on areas with clear business benefits. At the same time, the manager can justify what he would consciously forego.
What makes us skeptical: If possible, everything should be implemented at the same time or the argument remains technology-driven without clearly stating the expected business benefit.
What we look for: Learning agility, curiosity and the ability to transfer patterns to your own business.
What convinces us: The manager shows, for example, which developments in healthcare, retail or the software industry could change their own business in the future and derives concrete consequences from them.
What makes us skeptical is that the view remains limited to one's own industry, or trends are described without classifying their importance for one's own business.
What we look for: Leadership understanding and the ability to further develop organizations.
What convinces us: The manager talks about new skills, continuous learning, changing roles and how people can work productively with AI.
What makes us skeptical: The answer boils down to productivity or job cuts. The development of employees hardly plays a role.
Red Flag: “Thanks to AI, we will need significantly fewer employees in the future.” If there are no statements about competence development or new value creation, this indicates a very narrow understanding of leadership.
What we look for: Change leadership, persuasiveness and the ability to shape cultural change.
What convinces us: The manager describes concrete measures on how to provide orientation, reduce fears, enable qualification and at the same time formulate clear expectations for the responsible use of AI.
What makes us skeptical: Skepticism is only understood as resistance that must be overcome. Leadership, dialogue and empowerment hardly play a role.
What we look for: independent thinking and strategic judgment.
What convinces us: The manager develops his own, well-founded perspective and questions common narratives. It can explain why, for example, technology is often overestimated, but the necessary change in leadership, culture or skills is underestimated.
What makes us skeptical: The answer mainly consists of well-known buzzwords or current hype. Your own position is not recognizable.
What we look for: integrity, a sense of responsibility and the willingness to take personal responsibility for far-reaching decisions, even in the age of AI.
What convinces us: The manager describes clear personal guidelines and makes it clear that AI can increase the quality of decisions, but that responsibility for critical decisions always remains with the manager. She can explain this clearly using a concrete example.
What makes us skeptical is that no personal guidelines are apparent, or responsibility is implicitly delegated to processes, algorithms or governance.
Red Flag: The manager bases his limits solely on regulatory or compliance requirements and not on his own responsibility or ethical judgment.
"AI will change - perhaps even replace - many management tasks. What it cannot replace is leadership responsibility. That is precisely why judgment is not becoming less important in the age of artificial intelligence, but rather is becoming the decisive core competency of successful managers. The best managers do not impress with the best prompts or the greatest technical detailed knowledge. They are characterized by the fact that they translate technology into better decisions, sustainable value creation and effective leadership."
