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If America Pulls the AI Plug This is How Companies Become Independent

By Neurawork | Translated by AI 2 min Reading Time

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The temporary shutdown of the AI model Claude Fable 5 has sparked a discussion about dependency on single AI providers. For the AI consultancy Neurawork, the case highlights one thing above all: companies need a sovereign AI strategy that is not dependent on a single provider, model, or legal system.

(Image: Neurawork AI / Leonardo.ai / AI-generated)
(Image: Neurawork AI / Leonardo.ai / AI-generated)

"Many companies are currently focusing on the question of which AI model is the most powerful. However, the more important question is: What happens to my processes if this model is no longer available tomorrow?" says Christoph Knöll, founder and managing director of the AI consultancy Neurawork.

From Neurawork's perspective, the case of Claude Fable 5 exemplifies that the availability of AI systems can increasingly become an operational risk. Data sovereignty, compliance, and reliability are therefore no longer side issues but central prerequisites for the productive use of AI.

Therefore, the company has developed a concept called 'Operational AI,' which aims to help companies build AI applications that are more independent, reliable, and economical. The concept is based on four steps:

Step 1: Identify economic bottleneck

At the beginning, it's not about the technology but the economic question. Companies should first analyze which bottleneck has the greatest impact on revenue, costs, or growth. Only then should it be examined how AI can assist in solving the issue.

Step 2: Fully understand processes

In the second step, the relevant process is analyzed in detail and broken down into individual work steps. The goal is to determine where AI truly adds value and which tasks can be automated without large AI models.

Step 3: Build architecture with sovereignty

The next step is to develop the technical architecture. Neurawork recommends incorporating open technologies, European infrastructures, and specialized systems. High-performance language models should only be used where they provide real added value.

Step 4: Integrate governance and reliability

In the final step, compliance, data protection, EU AI Act, GDPR, as well as technical fallback options are taken into account. This is to ensure that the failure of a single provider does not bring entire processes to a halt.

"Most companies think of AI in terms of models first. We recommend starting by thinking about your own processes. Those who understand their workflows depend much less on individual platforms and can use AI more economically at the same time," says Knöll.

According to Neurawork's assessment, the companies that will gain competitive advantages in the future are those that view AI not as an isolated tool but as an integral part of a sovereign and resilient corporate architecture.

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