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Sovereignty in the Age of AI: What Banks Can Actually Decide

Posted on 02.06.2026 By Stefanie Auge-Dickhut

How sovereign are banks really when it comes to the use of artificial intelligence?

Many institutions are investing heavily in AI. But the real question is no longer which application to implement, but where genuine strategic freedom still exists.

Our latest article explores:

• Why banks are becoming increasingly dependent on a small number of providers for chips, infrastructure, and standards
• Why dual sourcing may reduce outages, but does not create strategic independence
• Why proprietary data has become the most important lever for differentiation
• What role European AI models, cloud providers, and regulatory initiatives can play

The key distinction is no longer “make or buy”, but:
A redundancy strategy against outages — or a sovereignty strategy against loss of control?

How high is AI sovereignty currently on your institution’s agenda?

AI, All, Data, Digitization, News, Nicht kategorisiert, technologies

Data strategy in connected business models

From 2019 to 2024, the global volume of digital data generated or replicated annually almost quadrupled – a trend expected to persist (Tenzer, 2024). Technology companies are demonstrating how data is being used to generate revenue that often dwarfs physical assets. Neglecting data can put companies at a significant disad-vantage in the future, leaving them behind data-driven competitors. However, many companies do not utilize the majority of their data and face issues such as data breaches and data silos (DalleMule & Davenport, 2017). The key is to develop and implement data strategies. This blog post presents a categorization for data strategies and their relevance for digital companies and banks in particular.