Das schnellste Pferd am kaputten Karren

Late last year, Forrester reported that only 15% of decision makers saw AI actually improve their bottom line. Businesses reacted by delaying 25% of their planned AI spending to 2027. And the analysts keep landing on the same cause.

The data was never ready.

It's like buying the fastest racing horse on the market, then hitching it to a cart with a missing wheel.

The horse can't move, but everyone stands around blaming the horse.

This isn't a new story.

We saw the same rollback with machine learning, and with data science before that.

Now the advice being sold is to add more horses: more agents, more tokens, more compute.

As if scale will drag a broken cart down the road.

It won't.

People treat AI like a database, something you can pull answers out of.

But really, it's a processing unit: it transforms whatever you feed it.

Put the best AI in the world on messy data, and you get messy results, just faster.

It's the same for manufacturers. Feed weak steel into the best CNC machine, and it breaks or fails to do what it should.

The raw material defines the quality of everything that comes after.

Care about that first, and the agents take care of themselves.