Beyond the Hype: How local regulations shape AI
If you’re tight on time, no need to prompt an LLM to read this for you (we did it already). So, TL;DR:
Regional regulations profoundly shape how AI systems are designed, used, and trusted. While the EU, US, and China legislate for AI safety and trust, each does so from distinct ethical and cultural perspectives. Research from Renessai highlights both overlapping and uniquely interpreted values across these regulatory blocks, which leads to real-world friction and missed opportunities for innovation.
Effective global AI requires more than technical excellence. We at Renessai call for value-sensitive global standards that enable both innovation and alignment – ensuring AI works for everyone, everywhere.
Regulations around the world reflect what’s fair
To stay ahead, organizations must do more than just innovate and learn how to apply AI in their core functions. They must foster understanding across these invisible but powerful regulatory divides.
Even though technologies are merely tools, neutral in their foundations, combining a LLM to a system is not, because it requires designing how it functions.
Artificial Intelligence Systems are not just lines of code or engines of productivity, they are a direct reflection of the values and rules upon which they are built.
Around the world, regulators are embedding their priorities into AI frameworks, setting not just constraints but fundamentally different ideas of what is "acceptable" or "fair".
At Renessai, we recognize that while the EU, US, and China all legislate for safety and trust, each does so from a distinct ethical foundation and worldview. Recent research (Gonzalez Torres & Ali-Vehmas, 2024) by our independent AI legal expert Ana Paula has highlighted the difference between AI-related regulatory values in these regions. It is clear that some values overlap between the three different regulatory contexts (e.g., rule of law). However, there are values which are specific to their own regulatory contexts (e.g., opportunities to all to pursue their dreams, equality, prosperity). Similarly, the specific conception of values is subject to varied interpretations.
AI "thinks" differently across borders – and why this matters
The rules, assumptions, and values driving a European-designed medical AI can diverge sharply from those shaping an American hospital’s ethics or from what’s hardcoded into a Chinese smart home device operating in Finland. These are not just theoretical issues: if one system prioritizes patient privacy above all, and another values operational efficiency or social cooperation, they may deliver conflicting recommendations, or worse, refuse to work together entirely.
If these digital systems cannot "speak the same language" regarding values such as privacy, equity, risk, they might pose real threats to effective healthcare, security, and user experience. Imagine the confusion when a medication recommendation derived from European regulations is rejected by an American clinical system as incomplete or inappropriate. Or the frustration when a cutting-edge device from Asia is unable to connect with European smart ecosystems due to regulatory misalignment.
We see this already, from high-profile cases like Apple Intelligence’s limited release to quiet frustrations as smart devices fall short of full functionality in new regions.
What we suggest moving forward?
Without shared, value-sensitive standards, each new regulatory rule becomes a potential barrier rather than a bridge. The path forward requires honest, boundary-breaking solutions and advocacy for global standards that respect both innovation and the cultural contours that define fairness.
One possible solution is to establish AI-value sensitive standardisation which would touch upon regulation, design and development of AI-based systems (Gonzalez Torres & Ali-Vehmas, 2025).
