AI Dependency as an Operational Risk: Four Steps Toward Greater Data Sovereignty

The temporary shutdown of the AI model Claude Fable 5 has sparked a discussion about reliance on individual AI providers. For the AI consulting firm Neurawork, this case demonstrates one thing above all: Companies need a robust AI strategy that isn’t dependent on a single provider, model, or legal system.

«Many companies are currently focused on which AI model is the most powerful. The more important question, however, is: What will happen to my processes if this model is no longer available tomorrow?» says Christoph Knöll, founder and CEO of the AI consulting firm Neurawork.

The Availability of AI Systems as an Operational Risk

From Neurawork’s perspective, the Claude Fable 5 case serves as a prime example of how the availability of AI systems can increasingly become an operational risk. Data sovereignty, compliance, and reliability are therefore no longer secondary issues, but rather key prerequisites for the productive use of AI.

That is why the company has developed «Operational AI,» a concept designed to help companies build AI applications that are more independent, more reliable, and more cost-effective. The concept is based on four steps.

Step 1: Identify a financial bottleneck

The starting point is not the technology, but the business challenge. Companies should first analyze which bottleneck has the greatest impact on revenue, costs, or growth. Only then should they examine how AI can help solve the problem.

Step 2: Fully Understand the Processes

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

Step 3: Build the Architecture with Confidence

Next, the technical architecture is developed. 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 Resilience

The final step takes into account compliance, data protection, the EU AI Act, the GDPR, and technical workarounds. This is intended to help companies prevent the failure of a single provider from bringing entire processes to a standstill.

«When it comes to AI, most companies think of models first. We recommend starting by thinking about your own processes. If you understand your workflows, you’ll be much less dependent on individual platforms and can use AI more cost-effectively at the same time,» said Knöll.

According to Neurawork, the companies that will gain a competitive advantage in the future are primarily those that view AI not as an isolated tool, but as an integral part of a robust and resilient corporate architecture.

More information: www.neurawork.ai

This article originally appeared on m-q.ch - https://www.m-q.ch/de/ki-abhaengigkeit-als-betriebsrisiko-vier-schritte-zu-mehr-datensouveraenitaet/