Search
Standard Chartered Equity Chief Investment Officer Sundeep Gantori noted that the AI investment theme is shifting from hardware infrastructure to services, platforms, and energy. In Asia, China focuses on "tools," India on electricity, and other regions on platforms. This shift will reshape the business models and competitive landscape of the global digital economy.
Over 200 economists and researchers, including 15 Nobel laureates and experts from OpenAI, Anthropic, and Google, are jointly calling on governments and technology leaders to urgently formulate policies to address the economic impact of AI, warning that the speed of AI transformation may far surpass that of the Industrial Revolution.
Based on U.S. labor data, the technology and finance sectors are losing 28,000 jobs per month due to AI, analyzing the deep impact of AI on employment structure, business models, and the global digital economy.
June 2026 marks the shift of AI governance from policy discussions to practical operations. This article analyzes key events such as the Anthropic/Alibaba distillation accusations, U.S. model access controls, and OpenAI's phased releases, revealing how model access has become the new geopolitical control point after chips, and how data, energy, and cybersecurity are reshaping the digital economy landscape.
Agentic AI is moving from concept to enterprise-level deployment, giving rise to new business models and investment logic. This article analyzes how the application layer can absorb infrastructure investment and evaluates its economic impact.
The traditional FAANG combination is being replaced by MANGOS (Meta, Anthropic, Nvidia, Google, OpenAI, SpaceX). IPOs of AI and space companies will redefine the growth engines and business models of the digital economy.
The generative AI in agriculture market is expected to grow from $280 million in 2025 to $930 million in 2030, at a CAGR of 27.2%. The proliferation of this technology is reshaping core areas such as precision agriculture, climate prediction, and pest detection, driving the transformation of agriculture from traditional experience-based models to data-driven platforms. This trend not only impacts global food security but also has profound implications for the platform economy, AI commercialization, and cross-border data governance.