Core Insights - The Chinese AI Infrastructure as a Service (IaaS) market is projected to grow by 122.4% year-on-year, reaching 19.87 billion by the first half of 2025, driven by the demand for AI capabilities across various industries [1][2] - Alibaba Cloud leads the market with a 24.7% share, excelling in both Generative AI IaaS and Other AI IaaS segments [1] - The Generative AI IaaS segment is expected to account for over 80% of the AI IaaS market, with a staggering growth of 219.3% year-on-year [1] Market Dynamics - The demand for AI services is robust across multiple sectors, including internet, automotive, mobile manufacturing, finance, and government, with automotive companies intensifying competition for smart driving solutions [2] - Alibaba Cloud has established partnerships with major Chinese automotive manufacturers, such as FAW, BYD, Geely, NIO, and Xpeng, to enhance their smart capabilities [2] Future Projections - The importance of inference infrastructure, necessary for running AI agents, is expected to significantly increase, becoming a core component of AI cloud services [2] - The overall AI infrastructure market is anticipated to approach 150 billion by 2029 [2]

Core Insights - The overall AI IaaS market in China is expected to grow by 122.4% year-on-year, reaching a market size of 19.87 billion RMB by the first half of 2025 [1] - The GenAI IaaS market is projected to grow by 219.3%, with a market size of 16.68 billion RMB, while the Other AI IaaS market is expected to decline by 14.1%, reaching 3.19 billion RMB [1] Market Overview - The AI IaaS market is experiencing explosive growth, driven by strong demand across various sectors including internet, automotive, mobile manufacturing, finance, and government [5] - Cloud service providers have significantly increased capital investment in AI infrastructure, leading to stable resource supply and pricing in the computing market [5] - The demand for intelligent computing and AI applications is rising, particularly in the automotive sector, where competition for autonomous driving solutions is intensifying [5] GenAI IaaS Market Dynamics - The focus in the GenAI IaaS market is shifting from large-scale model training to inference, with inference scenarios accounting for 42% of the market share in the first half of the year [6] - The DeepSeek event has positively impacted the market, with significant deployments in state-owned enterprises and government sectors nearing completion [6] - Major enterprises are beginning to test generative AI applications within their business systems, indicating a shift towards more diverse AI applications [6] Supply Landscape - The supply landscape is evolving towards a diversified ecosystem, with cloud vendors and leading computing clients focusing on optimizing inference service cost structures [7] - Domestic and international cloud computing companies are increasingly investing in self-developed chips, signaling a new growth phase for domestic computing resources [7] Competitive Landscape - The GenAI IaaS market share has risen to 84%, while the Other AI IaaS market share has dropped to 16%, indicating a concentration of market power [9] - Alibaba Cloud maintains the largest market share by increasing capital expenditure on AI infrastructure and offering diverse AI IaaS services [9] - Other players like ByteDance's Volcano Engine and Baidu are also expanding their market presence through competitive pricing and technological advantages [9] Operator Developments - Major telecom operators are rapidly deploying intelligent computing resources, with significant growth in AI-related business [10] - China Telecom is building a distributed intelligent computing network, while China Mobile and China Unicom are enhancing their AI capabilities and service offerings [10] Future Projections - The AI IaaS market in China is expected to continue its rapid growth, potentially reaching nearly 150 billion RMB by 2029, with inference computing accounting for nearly 80% of the market [12] - Technological advancements in multi-modal models and video generation models are anticipated to drive new AI applications and further increase demand for AI computing resources [12]