Policy desk

AI companies must comply with requirements for controlling superintelligence development

AI companies must establish internal control mechanisms to ensure AI system safety

Tech companies must self-regulate AI technology to ensure safe development

Companies must establish internal mechanisms to monitor AI model behavior

Companies must establish robust AI safety control systems with dedicated teams

Companies must hire independent auditors to evaluate AI systems

Provides a more convenient access channel for government services, improving user experience

Must establish comprehensive AI security incident reporting mechanisms to ensure timely disclosure of all unauthorized access attempts

Provides government funding opportunities for AI companies in healthcare applications

Google must provide access to certain data and services to competitors, altering its market behavior

Research institutions need to increase AI R&D investment, particularly in foundation models and intelligent scientist systems

Operators can formally apply for commercial autonomous vehicle operations, moving beyond pilot programs

Companies must strengthen core technology R&D in multi-sensor fusion, algorithms, solid-state batteries, automotive chips, and operating systems

Dutch government will gradually reduce reliance on Microsoft products, shifting to NixOS-based autonomous solutions

U.S. AI companies must adjust model release processes to ensure U.S. agencies review first

AI companies must adjust model release processes to ensure U.S. government gets priority testing access

Financial institutions must provide AI skills training to employees to maintain competitiveness

AI elevated to strategic priority level, indicating future policy support and funding

Provides funding support for AI evaluation research and promotes academic collaboration

Data center operators must disclose their energy and water consumption data

Mobile on-device AI service providers must complete registration to operate in China

Provides traceability for AI-generated content, helping identify content sources

Manufacturing enterprises are required to accelerate the application of AI in R&D design, production manufacturing, and management operations to enhance digitalization and intelligentization, aligning with national industrial policy directions.

Obligations: Enterprises must invest in building an organizational ontology to provide context for AI agents. • Opportunities: A well-defined ontology enables more effective AI-driven automation and decision-making. • Deadlines: While not explicitly stated, the guide implies a need for immediate action to catch up with the pace of AI-driven network attacks.

E-commerce and livestream platforms must adopt AI technology to strengthen compliance and prevent issues like counterfeit products and price fraud

Companies must strengthen AI-manufacturing integration, developing smart factories and intelligent manufacturing solutions

Obligations: AI companies may face legal scrutiny and potential penalties if found to have coordinated to limit AI development speed, violating antitrust laws. • Opportunities: The case highlights the importance of transparent communication and compliance with antitrust regulations in the AI sector. • Deadlines: The court case is ongoing, with the possibility of a collective class-action suit being certified, which could impact the companies' operations and public perception.

Data center development approval processes will slow down, requiring companies to adjust project planning and timelines

Obligations: AI companies operating in California may be subject to new regulatory requirements, including potential mandatory security audits by independent third parties. • Opportunities: Companies may gain clarity in the regulatory framework for AI safety, potentially reducing uncertainty. • Deadlines: Companies should prepare for the upcoming two-month timeline for the expert panel to submit its recommendations and the subsequent legislative process.

Obligations: Companies must comply with new evaluation standards for token factories, focusing on core technical metrics like model adaptation capacity and energy efficiency. • Opportunities: Firms with leading token factories can receive government support. Companies involved in model technology iteration, chip adaptation, and overseas service development can tap into new market opportunities. • Deadlines: The plan is set for implementation from 2026 to 2028, with specific milestones for building factories, launching platforms, and achieving technology breakthroughs.