Brainfood

When talking about AI and leadership, the debate almost always revolves around tools, skills, or the “right” leadership style. What is often overlooked is that the real lever is not the personality of individual leaders, but the system with and inwhich leadership is exercised.

And why it is the responsibility of management to prevent this.

Anyone talking about “leadership and AI” today quickly ends up comparing tools or offering prompt tips. That's not the core issue.

AI does not replace leadership. However, it does change the conditions under which leadership operates.

In many organizations, leadership has long been closely linked to a knowledge advantage. This foundation has been crumbling for years due to teams of experts, more complex and faster markets, and highly specialized employees. With AI, it is finally falling apart: knowledge is suddenly widely available and ultra-fast. And it is not always 100% reliable.

Therefore, it is not information that is becoming scarce, but orientation and the extent to which we evaluate.

Researchers at Stanford University describe this change: Artificial intelligence is not just another tool in the leadership toolbox; it is increasingly becoming part of the strategic architecture itself. According to Stanford, leaders will be less concerned with gathering or evaluating information in the future. Their responsibility will be to decide what AI is used for, what questions it should answer, and what limits apply.

AI shifts the focus from “having knowledge” to “providing direction.” It makes decisions more data-rich, but not automatically smarter. This is where leadership in the true sense begins.

This brings us to the first point: Good leadership today does not mean knowing the most, but staying the course even when AI seems to know all the answers.

1. Leadership provides orientation in the age of AI

In this context, leadership means holding the compass while AI provides the data.

Stanford refers to this as “human-centered AI leadership.” Leadership that does not replace technology, but gives it a place in the system without relinquishing responsibility.

In other words, AI should (and must) provide the input. But orientation remains human.

And the guiding principle for this is the corporate strategy. It serves as a guideline for all decisions.

Leadership in this view translates the strategic direction into clear team decisions: What do we use our resources for? What do we leave out? What criteria apply when AI shows us several paths?

Strategy thus becomes a lived decision-making logic and thus even more central.

2. Leadership shapes decision-making processes when dealing with artificial intelligence

AI provides suggestions, but does not take responsibility itself.

If this gap remains open, gray areas arise: Who decides? On what basis? With what consequences?

And this is precisely where the second function of leadership in the AI age comes in: Leadership designs the decision-making architecture:

• What challenges do we have to face, what questions need to be answered?
• Which decisions remain fundamentally human?
• Where does the team use AI as input, where for preparation, where for acceleration?
• Who signs off on decisions and how is this documented?

3. Leadership as an even more essential cultural and ethical anchor in the use of AI

AI accelerates work, but it also amplifies what is already there: good structures and weaknesses alike. Trust or mistrust.

2 examples:

1. In one company, AI was used to automatically evaluate project progress. In teams with clear responsibilities, this worked extremely well, as transparency helped to make decisions faster. In teams with unclear roles, however, the same tool led to conflicts: employees felt controlled and mistrusted the data.
2. A manager uses AI to support personnel decisions based on data. Those who trusted the manager and believed that the chosen tool was carefully selected and “aligned with the company's values” saw an increase in the quality of decisions. Others who lacked trust perceived the same application as surveillance, and as a result, employees withdrew.

AI is not a neutral accelerator. It reinforces the culture it encounters. If structures are clear and relationships are stable, AI makes everything faster. If they are fragile, it only makes the cracks more visible. And: The biggest differences in the effectiveness of AI arise not from technology, but from the context in which it is used (SHRM, 2024).

In this environment, leadership is needed as an anchor:

• Culturally: What applies in our company when things have to move quickly?
• Ethically: Where do we draw the line, even if something is feasible?
• Socially: Who is heard, who falls through the cracks when AI dominates?

AI does not lead. But it changes the situation in which leadership must show attitude.

Conclusion: Leadership retains its significance through attitude, direction, and clarity in the age of AI.

AI reveals which leadership styles are effective when knowledge is everywhere, the pace is increasing, and responsibility can easily “disperse.”

What is needed is orientation based on strategy, clear decision-making architecture, and cultural anchoring.

This is the lever that allows leadership to retain its significance and impact.

Outlook for Part 2:

The next article will focus on: When AI blocks instead of liberates. (And it is the task of leadership to prevent this.)

Sources:

https://www.clearadmit.com/2025/06/ai-management-and-innovation-insights-from-a-stanford-gsb-professor/

https://www.mckinsey.com/capabilities/tech-and-ai/our-insights/superagency-in-the-workplace-empowering-people-to-unlock-ais-full-potential-at-work

3 ideas for your organization:

1. Leadership requires strategic orientation rather than just a knowledge advantage
2. Decision-making processes must be designed and managed with AI in mind
3. Cultural and ethical clarity strengthen the effective use of AI

Reflection question:

Which of these ideas are relevant to your organization—and where could you start?

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