What matters now is not to become dependent on particular AI models. For every use case, pick the model and the vendor best suited to it. The most capable solution is not always the one that makes the most sense economically and strategically. Only then can companies really secure cost control, transparency, technological interchangeability, long-term scalability and, in the end, their own sovereignty.
We have spent a lot of this podcast on the technology and on the effects of AI. In episode 7 of Prompt & Proper, Steffen Ochsenreither from Swiss Post and I take on the transformation itself. Not what AI does inside a company, but how you point a company at AI. The episode is in German, and this post captures the core of the conversation.
As Chief AI Officer I am supposed to put an AI strategy in place, and the headline alone turns into work. AI-First, AI-Native, AI-Enabled, AI-Ready, AI-Shaped, AI-Augmented. In episode 6 of Prompt & Proper, Steffen Ochsenreither from Swiss Post and I go through the terms and end up somewhere the question does not suggest. The episode is in German, and this post captures the core of the conversation.
AI portfolios rarely fail because leaders lack ideas. They fail because too many initiatives are funded before anyone proves they can move a business metric, fit into a real workflow, or survive enterprise constraints.
