At AIBank, the delegation was introduced to the bank's robust use of AI and cloud-native infrastructure to create a secure and highly scalable digital banking platform. Since its establishment in 2017, AIBank has experienced rapid growth, operating at a scale that serves a hundred million customers across China. A key focus of the discussion was the bank’s operational resilience, which is supported by an advanced microservices architecture that ensures high system availability—vital for handling over millions of daily transactions with minimal downtime.

AIBank’s ability to maintain operational continuity while addressing significant cybersecurity challenges (handling thousands of cyberattacks each day within seconds) was highlighted as a critical competitive advantage. This combination of technological robustness and AI-driven service models has allowed AIBank to become a profitable venture, leveraging data to provide tailored products in wealth management, consumer finance, and business loans. The bank’s profitability, coupled with its operational resilience, has made it a key player in China’s rapidly growing digital banking sector.

At ChinaAMC, delegates were provided with a comprehensive comparison between the development of foundational AI-generated content (AIGC) models in the United States and China. While China has made considerable progress, it was highlighted that there remain gaps between the two countries. These gaps are largely due to limitations in edge-side hardware capabilities, such as GPUs (graphics processing units), NPUs (neural processing units), and GLUs (graphical learning units)—all critical for training and deploying large-scale AI models.

The discussion brought attention to the fact that while China is advancing rapidly in AI model development, it faces challenges in producing the high-performance hardware required to run these models efficiently. Chinese companies are making strides in AI-driven technologies, but reliance on foreign-made advanced semiconductors and chipsets still poses a challenge, especially given geopolitical tensions and trade restrictions. Delegates learned about China's efforts to develop homegrown solutions through firms such as Huawei, Alibaba, Cambricon Technologies and Horizon Robotics, etc, which are working on AI chips but still trail global leaders like NVIDIA, Qualcomm and AMD, in terms of performance.

ChinaAMC emphasised the critical role of these hardware technologies in shaping the future of AI in China. The success of foundational AIGC models—like those being developed in natural language processing and image recognition—hinges on the country's ability to close these hardware gaps. The future of AI in China, therefore, depends not only on the development of sophisticated software models but also on the country’s ability to produce cutting-edge semiconductors that can power these advancements.

Day 2 of the tour offered a diverse and insightful look at how AI is influencing not only financial services but also transportation and investment strategies in China. From AIBank’s pioneering use of AI for operational resilience and scalability, to ChinaAMC’s focus on AI-powered investment in sectors like edge-side chip manufacturing, the delegates were provided with a comprehensive view of China's technological ambitions and its broader economic potential.