How Data Sovereignty Is Reshaping AI Strategy And Software Development

Global politics has always been one of the forces that dictates progress and technology distribution. If at the beginning of the millennium we saw borders open and knowledge shared, now the situation has reversed.

International tensions and data protection laws lead to countries shutting their borders and imposing limitations on developers and everyday users. The rise of AI in the 2020s complicates everything even further; AI trains on large datasets, which were previously unregulated.

Countries seek to reduce their dependence on foreign technologies. Digital sovereignty has accelerated in response to geopolitical tension and sanctions.

The Start Of Digital Segregation

Historically, countries have imposed technology restrictions. However, at the beginning of the 2010s, the internet was more open than now. Global platforms operated with minimal regional restrictions; it was the age of international business. Cross-border data flows let the digital economy flourish.

But due to conflicts, the U.S. and the EU have expanded sanctions against several states since 2014, with major escalations taking place in 2022.

As a result, many tech companies withdrew from markets such as Russia and Belarus. Similar restrictions were inflicted on China (including the Huawei ban and TikTok restrictions), Venezuela and Myanmar and others.

This vacuum has pushed local developers to build alternatives. China's "Great Firewall," combined with restrictions on foreign platforms and broader state digital policies, helped drive the growth of domestic services such as WeChat, contributing to the development of a largely self-contained digital ecosystem. Now, something similar is happening worldwide.

How End Users Respond: The Rise Of VPN

Despite governments trying to limit access to foreign technology, users seek tools to access it, whether to get better pricing for subscription services or to access content that is blocked otherwise. VPN adoption increased in countries like the Netherlands and the UAE.

The demand for VPN and proxy services tends to spike whenever governments tighten controls.

The Great Firewall Expands

In China, websites operating commercially typically must obtain an ICP filing or license, and the country's cybersecurity and data-protection laws impose localization requirements for certain categories of data, particularly sensitive or strategically important information. Before, it was a relatively rare case. Now, this pattern spreads—data must often remain within national borders. For example:

After that, dozens of economies have expanded their own data-protection rules, including Brazil's LGPD and California's CCPA/CPRA. The result is that it's more difficult than ever for international businesses to process their clients' data.

Leaders should design data architecture regionally from day one. Separate storage zones per jurisdiction, not as a single global database, to avoid costly retrofitting when new data localization laws unexpectedly launch.

AI Vs Data Protection

These same regulations create challenges for companies integrating AI into their products. AI systems require large amounts of user data to function, but privacy laws limit how it can be stored and where it can be processed.

For example, Site.pro develops global accounting software, but we cannot rely on one AI model for all markets. Financial data is extremely sensitive and has more limitations in terms of what can and cannot be processed outside of the country's borders. A Chinese AI model doesn't meet EU regulatory requirements, while a U.S. model may conflict with the privacy frameworks of Eastern Europe, the Middle East and Asia.

Website-building tools face fewer restrictions because they process less personal data. Still, the direction is clear: Global AI deployment is becoming more expensive and dependent on local laws.

AI Becoming Localized

When we participated in CloudFest 2026, we met multiple potential partners that expressed interest in partnering with tech companies based in politically neutral jurisdictions, like ours.

Being a Europe-based company has a competitive advantage in a European market, as several potential partners shared concerns about relying on U.S.-based AI because of regulatory risk, costs and potential sanctions.

At the same time, the most advanced AI models—such as OpenAI, Google and Anthropic—dominate the market. A lot of businesses rely on the OpenAI LLM model, but it seems like more and more of them are exploring alternatives. We were even asked whether our AI website builder supported custom LLMs keys so a hosting company could stay independent.

Ideally, AI vendor selection should be jurisdiction-aware:

A Potential Return To On-Premises

Ironically, technologies once considered outdated are regaining relevance. On-premises software, which allows all data to be stored on local devices, is becoming attractive for governments and businesses. There are even considerations regarding moving AI projects to private infrastructures to cut costs and avoid risk.

Cloud will probably remain popular for a while, but software is moving toward hybrid or fully local deployment. Digital borders are becoming more rigid, and the global technology ecosystem is breaking into smaller regions.

The era of the globally unified web is coming to an end, at least for now. On one hand, geopolitical restrictions create a lot of inconvenience for businesses and regular people. On the other hand, they can stimulate growth and competition.

Contracts and compliance strategies should keep evolving. Businesses are often frustrated by the need to standardize data processing agreements by jurisdiction rather than by vendor, incorporate audit rights across both cloud and on-premises deployments and schedule ongoing compliance reviews as new data regulations emerge across different markets.

We must never stop looking for alternative solutions. Our team, and many of our partners and competitors, are considering training their own localized AI. Who knows, maybe homemade LLMs will compete with OpenAI in speed, quality and price for similar tasks?

Original publication: 2026-06-08 How Data Sovereignty Is Reshaping AI Strategy And Software Development