Artificial intelligence is evolving at breakneck speed, and governments across the world are racing to build regulatory frameworks that promote innovation while safeguarding public interest. A diverse array of AI governance models now exists, each reflecting the distinct values, strategic goals, and societal concerns of its region. From ethical oversight to data transparency, these frameworks signal a global shift toward more accountable and inclusive AI development.
What are the Global AI Regulation Frameworks in 2025?
The Global AI frameworks below were established to identify a balance between promoting innovation while maintaining ethical principles and the health of society.
1. European Union: Artificial Intelligence Act (EU AI Act)
The EU AI Act has been in effect since August 2025 and has established four levels of risk for AI systems, ranging from low to high, to support AI governance. High-risk categories, such as biometric surveillance and critical infrastructure performance, have several requirements, including transparency, accountability, and human oversight. Fines for violation of these requirements can be as high as €35 million or 7% of global income.
Key Features:
- Risk-based classification of AI systems.
- Mandatory transparency and accountability measures.
- Enforcement through national authorities.
- Severe penalties for non-compliance.
2. United States: State-Level Initiatives and Executive Actions
While there is no comprehensive federal AI policy, states like California are taking matters into their own hands by drafting their own laws. One such law is California’s Senate Bill 243, which requires that AI chatbots inform users of their non-human identity. Moreover, in January 2025, Executive Order 14179 directly gave the U.S. a competitive edge in AI by endorsing the creation of non-ideologically biased systems.
Key Features:
- State regulations address AI applications.
- Executive actions to promote AI development.
- Innovative leadership in AI.
3. China: Centralized AI Governance
The governance of AI in China emphasizes centralized decision-making, giving top priority to maintaining social order and advancing the economy. The authorities mainly control the use of AI in areas they regard as sensitive, allowing various technologies to emerge, but only to the extent that their existence aligns with the state’s interests and morals.
Key Features:
- Centralized regulatory framework.
- Emphasis on social stability and national interests.
- Control over AI deployment in sensitive sectors.
4. United Kingdom: Agile and Sector-Specific Regulations
In the UK, a sector-specific, flexible approach to AI regulation is used, ensuring each sector can have an individually tailored oversight; thus, healthcare, finance, and transport will be treated very differently according to their needs. The quick adaptation of regulators to technological changes, however, does not mean that risks will not be effectively controlled.
Key Features:
- Sector-specific regulatory frameworks.
- Emphasis on rapid adaptation to technological changes.
- Balancing innovation with risk management.
Conclusion
International AI regulations are now highly diverse, with four regions each implementing their own frameworks, priorities, and challenges. The European Union (EU) focuses on minimizing risks and has established strict regulations to that end. In contrast, the United States primarily relies on decentralized regulations determined by individual states. China, with its centralized governance, emphasizes stability in its approach to AI. Meanwhile, the United Kingdom is adopting rapid, sector-specific regulations. These varied approaches reflect a global recognition of AI’s influence and the necessity for responsible governance.