Digital Sovereignty - a realistic Ambition?
- Claas
- 6 days ago
- 4 min read
Digital sovereignty sounds reassuring. But what does it really mean?
Digital sovereignty has become a comforting term. It shows up in strategy papers, CIO discussions, political statements and IT roadmaps. It promises control in an environment that feels increasingly complex and opaque.
At the same time, very few people can clearly explain what it actually means for a company. The word sounds strong, but the substance behind it is often vague. That gap between promise and reality is exactly what makes the term so attractive.
Why sovereignty does not really apply to companies
Taken literally, sovereignty means ultimate decision-making authority. The ability to define rules and enforce them, especially when things go wrong.
That definition fits states. It does not fit companies.
Companies operate inside legal systems, markets, supply chains and global technology ecosystems. Absolute digital sovereignty would require full control over infrastructure, software, hardware, data and enforcement mechanisms. That is not a realistic corporate scenario.
In that strict sense, digital sovereignty simply does not exist for companies.
Why the debate still matters
If sovereignty is unattainable, the obvious question is why the topic keeps coming back. The answer is that most organizations are not actually looking for independence. They are reacting to a more subtle shift. Decisions feel less deliberate. Control feels less explicit. Dependencies grow quietly, without anyone consciously choosing them.
Digital sovereignty, in this sense, is less a goal and more a signal. It points to a growing unease about who really decides and on what basis.
A typical company setup today
Look at a fairly standard enterprise environment.
Core systems are built on market leading platforms. Cloud infrastructure runs on hyperscalers. Data processing is compliant. Security controls are in place. Operations are shared between internal teams and partners. On paper, this looks solid and mature.
To make it concrete, such a setup usually includes:
ERP, CRM and collaboration tools from established vendors
cloud based infrastructure with high availability
standardized analytics and reporting capabilities
external partners supporting build and run activities
None of this is reckless. In fact, these choices are usually the result of careful evaluation.
Where the issues start to appear
The problem is not the setup itself. It is what slowly happens around it. Over time, certain patterns emerge.
Forecasts are no longer debated, they are accepted. Priorities are suggested by systems and rarely challenged. Business rules move into configuration layers and release cycles. Teams start to say things like “the system does not allow that” instead of “we decided not to do that”.
No single decision caused this. It is the accumulation of many small ones.
What changes is not the technology landscape, but the decision dynamic:
systems start to frame choices before people are involved
accountability becomes harder to trace
knowledge concentrates outside the organization
alternatives remain theoretically possible but practically painful
This is where dependency becomes relevant.
The real risk behind dependency
Dependency itself is not new. Companies have always depended on suppliers, technologies and partners. The risk emerges when dependency affects how decisions are made.
This typically shows up when:
decisions are hard to explain after the fact
responsibility is formally assigned but practically diluted
critical logic lives in platforms rather than in the organization
switching is discussed as an option but avoided in practice
These effects do not appear overnight. They develop gradually and often remain invisible until options are already constrained.
The central risk is not dependency itself, but the illusion that control still exists where it has quietly shifted.
Where dependencies actually matter
Much of the public debate focuses on infrastructure, cloud regions or provider nationality. These aspects are not irrelevant, but they are often overstated. In practice, the most consequential dependencies tend to arise elsewhere:
in decision logic, when systems effectively decide without clear ownership
in data usage, when it is unclear which data drives decisions and who is responsible for it
in business logic, when differentiation is deeply embedded in standard platforms
in know how, when only vendors or integrators truly understand how things work
Not every dependency is dangerous. Many are perfectly acceptable trade-offs. The critical question is whether they undermine a company’s ability to steer itself.
A necessary reality check
Not every risk justifies action. Geopolitical developments are emotionally powerful but rarely controllable by individual companies. Jurisdiction and regulation must be understood but cannot be shaped. Infrastructure choices are essential for operations but usually offer limited leverage for decision making.
By contrast, there are areas where intervention is both realistic and effective. These include clarity over decision authority, ownership of decision relevant data, governance structures and explicit accountability for what is delegated to systems and what is not.
This is where effort tends to pay off.
What this does not imply
The conclusion is not to avoid hyperscalers, replace standard platforms or pursue symbolic technology choices based on origin. These moves are expensive, slow and often miss the underlying issue.
The challenge is rarely about choosing different tools. It is about using existing ones more deliberately.
What it does imply
A more mature response starts with a few uncomfortable questions.
Where are systems allowed to decide, and where should they only support human judgment?
Which data actually drives decisions, and who owns its quality and use?
Which parts of business logic should remain under direct organizational control?
Which dependencies are consciously accepted, and which should be limited?
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