APPLY RATHER THAN WAIT

No lecture. No slides. Just one question the leadership team could not let go of: Not whether AI is coming – but what we do before it overtakes us. This is the moment I run these trainings for. When scepticism turns into real reflection. When leaders start applying what they have so far only heard about. When they get going instead of waiting.

Human & machine:

AI is not a better tool. It is a different way of thinking. If you see it as a faster Excel, you miss the point. AI does not only change the speed of decisions. It changes the quality of the questions we ask ourselves in the first place. It makes visible assumptions we have never voiced. It shows options we have never had time for.

But it does not judge. It is not accountable for anything. It does not understand the space in which a decision is really made. That remains human … and will stay that way. The question is not human or machine. The question is: how good is the combination of the two?

Why without slides

You can talk about AI at length. You only understand it once you work with it yourself. That is why my trainings rely on first-hand experience rather than abstract answers: leaders work directly with AI systems, on questions that genuinely concern them, and reflect together on what the results mean for their decisions.

The turning point rarely comes through an argument. It comes when someone sees the machine expose an assumption that was never voiced in the team. Or when it reveals an option there was never time for in day-to-day business. Then scepticism turns into curiosity, and curiosity into a willingness to pursue it in their own company.

What the machine can and cannot do

AI can open up information, recognise patterns and develop different perspectives on a situation. It can formulate counter-proposals, sketch scenarios and test arguments. That is a lot. But it is not the same as a decision.

A decision is made in a space the machine does not know: with people, history, loyalties and risks that appear in no dataset. On top of that comes a practical problem. AI also delivers answers that look plausible and are nevertheless wrong. If you work with it, you have to learn to examine its results critically instead of trusting them just because they are well phrased.

That is precisely why the combination is decisive. The machine broadens the view. Experience, creativity and judgement decide what holds.

What good collaboration looks like

A viable division of labour between human and machine starts with a clear question. Without one, AI mainly produces volume. With one, it becomes a sparring partner that spans options more broadly than a team could alone in the time available.

After that, a deliberate step back is needed: which results are convincing, which contradict our experience, and why? This reflection is not an add-on but the actual core. A leadership team that asks itself these questions regularly uses AI not as a faster Excel, but as a different way of thinking.

Key takeaways for leadership teams

• The best way to understand AI is to work with it yourself on real questions.
• The machine makes assumptions and options visible; judgement and responsibility remain with people.
• Plausible answers are not automatically correct answers and must be checked.
• What matters is not human or machine, but the quality of their collaboration.

Read here what to expect in the training and how we work with leaders on their own questions. Benefits and approach →

Source: Original on erwinhettich.com