Andreas Welsch

I'm competent in this role.

And now I need to relearn this.

By the way, I think it's never been a greater challenge and a greater opportunity at the same time than right now because of all these things that generative AI, agentic AI allow us to do.

So increasing levels of autonomy, increasing levels of automation in routine work, now also more complex tasks.

No longer just if this happens, then do that.

Yeah.

But definitely where it's more uncertain, where there's more variance in the information.

So a great time to look at this in this space, but also an important factor, again, to make sure your team members, your people are aware of what are you doing?

Why are you doing it?

How will it help them?

How will it positively affect them?

What is the change that we expect?

So people number is number one.

Number two, it always comes back to data.

And anything with AI, you always want and need to have data.

Early on when ChatGPT came out,

Vast parts of the industry were super excited, right?

All of a sudden, everything is in this model, in ChatGPT as a tool or in Cloud and Gemini and what have you.

But people realized very, very quickly that the results are pretty generic.

Even with good prompt engineering, if the model hasn't seen your industry or company-specific data, it will not be able to generate it the way that your employees can and the way that it needs to be generated or put into context.