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The EU AI Act, China's Generative AI Measures, and U.S. state-level legislation—global AI regulation is rapidly fragmenting. How can companies get ahead in multi-jurisdictional compliance? Drawing on the AI regulatory tracker report published by White & Case, this article reviews the trends and offers recommendations for response.
Eversheds Sutherland’s July 2026 “Global AI Regulatory Update” shows that global regulatory focus is shifting toward transparency requirements, with corporate compliance costs and strategic risks rising in tandem.
The 2026 World Artificial Intelligence Conference (WAIC) opened in Shanghai, with 29 countries signing the founding agreement of the World AI Cooperation Organization (WAICO), as the AI governance framework promoted by China runs parallel to the Western system. This article analyzes the deep impact of this event on the global AI industry, corporate compliance, computing infrastructure, and the competitive landscape, and explores the industry signals behind Huawei's Atlas 950 and AI Agent phones.
Based on CIO.com's in-depth reporting, this article examines the application potential of Agentic AI in enterprises, focusing on core scenarios such as software development, customer support automation, and customer relationship management, while analyzing its impact on the industry landscape and corporate strategy.
This article, based on the latest ICLG report, analyzes key developments in China's 2025 AI regulation from principles to implementation, including content labeling, protection of minors, security incident response, and tech ethics, and explores market impacts and corporate response strategies.
Deloitte releases its annual "2026 Technology Trends" report, interpreting enterprise AI applications, infrastructure investment, and competitive landscape changes from the perspective of the AI industry, and analyzing their implications for decision-makers and investors.
White Jade Law Firm published the "AI Watch: Tracking US Regulation" report, reviewing federal and state-level AI legislative developments and analyzing the profound impact of fragmented US AI regulation on enterprise-level AI deployment.
Observer has released its 2025 AI Power Index, listing 100 leaders shaping the future of artificial intelligence. This article interprets the list from an industry perspective, analyzing the distribution of AI power, the interplay between capital and ideas, and how businesses and investors should understand this landscape.
Analyze the behavior of OpenAI Agent on the Hugging Face platform and its implications for enterprise AI deployment; discuss the industry impact of giants like NVIDIA, Meta, and Microsoft supporting open-weight models; and methods for measuring AI environmental footprint.
A Columbia University report proposes an AI power gap index, which comprehensively measures the shaping power of tech giants, governments, open-source communities, and other entities on the AI ecosystem, revealing a trend of industrial power concentration.
Enterprise software is undergoing the biggest architectural transformation since SaaS, with intelligent agent applications shifting from record systems to outcome systems, automating complex business processes, and improving efficiency and decision quality. Taking Oracle Fusion as an example, it analyzes market impact, competitive landscape, and business insights.
Nature published a perspective article, proposing that understanding large language models requires distinguishing between human projection and machine cognition, and that the framework of machine empiricism may change the logic of R&D, investment, and evaluation in the AI industry.
This week, Korean AI startups raised over $120 million, led by Holiday Robotics' $103.4 million Series A, highlighting an investment boom in AI infrastructure, enterprise automation, and robotics. Meanwhile, South Korea and Saudi Arabia are exploring a joint deep tech fund, and vertical AI applications are accelerating deployment.
OpenAI, Meta, SpaceXAI, and Anthropic have successively released new models and features within 72 hours, pushing the AI model competition into a white-hot phase. This article analyzes the industrial logic behind this flurry of releases, the changes in the competitive landscape, and the implications for businesses and investors.
A study published in npj Digital Public Health systematically evaluated the performance of five mainstream LLM architectures in simulating vaccination decisions, revealing significant biases among models, with some exhibiting a pro-science tendency. This finding has important implications for AI applications in public health modeling, corporate decision simulation, and other scenarios.
This article focuses on the debate between AI context and real-time organizational truth, analyzing how enterprises can reduce their reliance on cutting-edge large models through context engineering and intelligent control to achieve sustainable AI implementation. It also explores new standards for measuring AI value—shifting from usage rates to business outcomes.
Based on analysis from Bloomberg Law, this article explores how enterprises can use a four-dimensional framework (geography, industry, stakeholder roles, and risk categories) to address increasingly complex AI regulations, and uses California regulations as an example to demonstrate the practical application of the framework.
Analyze the application challenges of AI governance in autonomous networks, discuss the EU AI Act, real-time monitoring, L5 autonomy, Asia's leading position, and trust issues, providing industry-level insights for enterprise decision-makers.