Policy desk

Compute capacity in Germany will expand significantly by 2030, giving companies deploying AI training or inference in Germany more local compute supply

Generative AI medical device developers can submit feedback during the open docket period and directly shape the future regulatory framework.

Mountain scenic areas in Shandong present procurement and deployment opportunities for hiking-assist robot vendors

Commerce and manufacturing companies can apply for inclusive computing power, 'specialised and sophisticated' enterprise status, and fiscal support under the 'AI + Manufacturing' action.

Foreign AI services must obtain Chinese AI approval before launching in China; Apple's approval provides a reference path for similar products.

Companies deploying AI agents in Singapore and the region can use the reference architecture to design inter-agent authentication and trust transfer, improving interoperability.

Licensed banks operating in Hong Kong must establish clear accountability mechanisms and ownership for AI systems under the ART framework

On-device LLMs offered in China must complete CAC filing before launch; devices without updated filings (e.g. iPhone 15/15 Plus) do not carry the AI features

Companies must comply with EU's agentic AI application guidelines

AI model developers gain a clear "AI + railway" application direction with operation and maintenance data scenarios for online safety assessment and intelligent O&M projects.

AI companies must establish security incident reporting mechanisms to ensure immediate reporting to the US government

Model developers will face questions from the EU AI Office regarding recent incidents and must cooperate with investigations

AI companies must establish model control and monitoring mechanisms to ensure technical safety

Companies need to align their business strategies with Hong Kong's AI development direction

Clear liability rules established for accidents involving autonomous vehicles

Financial institutions must establish AI risk management systems to ensure the safety, reliability, and explainability of AI systems

Medical AI product providers must prepare for upcoming FDA regulatory requirements

Requires AI companies to reassess whether their models meet the updated 'frontier model' definition

Companies must ensure AI applications comply with new regulations, avoiding excessive usage

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

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

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

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

Data centre operators must provide equivalent renewable energy to their power consumption, increasing operational costs

ADAS providers must enhance detection capabilities for stationary or slow-moving vehicles