The biggest misconception about AI

What AI Competence Really Means

Many people are currently talking about the ability to use AI effectively. And it often sounds as though it’s primarily about mastering tools, crafting prompts, or efficiently integrating applications into daily work routines.

Unfortunately, that’s far too narrow a view. Because when I look at how AI is currently finding its way into organizations, a very technical understanding of competence often emerges. Anyone who can operate a tool is considered competent. Anyone who delivers results faster is seen as particularly advanced.

AI is a helpful tool in many areas of our personal and professional lives. And so it is inevitable that it also changes how we think, make decisions, and assess reality. And with that, our understanding of what AI competence means is also shifting.

Prof. Dr. Yasmin Weiss aptly describes that AI competence only reveals its true value once we overcome our own initial hurdles and begin to truly transform the way we work—not just optimize it. This may sound simple at first, but its implications are far-reaching.

Because it shows that AI literacy isn’t something you “learn” once and then check off your list. Rather, it is a process—a constant balancing act between what the machine can do and what we, as humans, must take responsibility for.

Of course, this requires a basic understanding of AI—knowing how systems work, where their limits lie, and why results sometimes seem convincing even when they aren’t. Equally important is a sense of data—its quality, its context, and the risks associated with it.

However, the ability to use these tools effectively is, quite frankly, the easiest part.

The real challenge lies elsewhere.

It lies in the question of how we position ourselves within this new collaboration. What role we take on. Where we bear responsibility—and where we might be relinquishing it too quickly.

Because the better AI becomes, the more tempting it is to rely on its suggestions. That is precisely why critical thinking is becoming one of the most essential skills. Not in the sense of mistrust, but in the sense of context.

What is reliable? What is merely plausible? And where does my responsibility as a leader begin?

Added to this is a dimension that is often underestimated: the ethical one. AI does not make decisions in the true sense of the word. It calculates, combines, and predicts. We are still the ones who bear the consequences.

And at the same time, the boundary between human and machine is constantly shifting. What is clearly still our task today may be automated tomorrow. Here, we clearly need a high degree of flexibility: Where does AI help me? What can I actually do better or faster thanks to AI? And where does the advantage lie in combining my work WITH AI? Because this is constantly changing, I have to “stay on top of things.”

When I put all this together, one thing becomes very clear to me: AI competence is not a technical skill. It is a matter of attitude. That is why we are not focused on technology, but on leadership.

Why AI Is and Will Remain a Leadership Issue

Because leadership determines how AI is used within an organization. Whether it is deployed purely as a tool for efficiency or as a true thinking partner. Whether employees learn to question results or allow themselves to be guided by them. Or even create entirely new things that would not have been possible before.

I frequently observe that organizations are investing heavily in tools—but significantly less in what actually makes the difference: in orientation, reflection, and conscious decision-making. But that is precisely what distinguishes amateurs from professionals!

Because AI increasingly influences what we consider right, sensible, or relevant. Texts seem coherent, arguments logical, recommendations well-thought-out. Here we need a new form of presence or even of mindfulness.

The crucial question is not: How do I use AI? but rather: How do I know if I can trust it?

And raising awareness and training our teams in this area demonstrates true quality.

Or to put it another way:
Those who merely learn to use AI become more efficient.
Those who learn to think with it become more effective.