In 2026, venture capital in the global AI field continues the hot trend of the previous two years, but capital flows are undergoing profound structural changes. From basic large-scale models to vertical applications, from computing infrastructure to AI native tools, investment hotspots are rapidly rotating, showing a completely different pattern from the past.
The most significant change is the shift of capital from general models to vertical industry applications. Between 2023 and 2024, a large amount of funds will flow into the field of basic large-scale models, giving rise to a number of open-source models such as Llama, Qwen, DeepSeek, and others. By 2026, investors will focus more on how AI can solve specific industry problems - medical AI, legal AI, financial AI, and manufacturing AI will become the most sought after sub sectors. According to industry insiders' estimates, the total financing obtained by vertical industry AI applications in Q1 2026 has exceeded that of general large-scale model projects, marking a new stage of "landing is king" in the AI industry.
AI infrastructure and toolchain are another capital intensive area. With the acceleration of enterprise AI deployment, the demand for model training platforms, inference optimization tools, data annotation services, and MLOps platforms has surged. The sustained high growth of chip manufacturers such as NVIDIA has driven the emergence of computing startups, and a group of startups focused on AI chip design, computing power scheduling, and edge reasoning have received large amounts of financing.
It is worth noting that the concept of AI agents is becoming a new investment explosion point. From automatic code programming agents to enterprise process automation agents, investors believe that agents are the key transition of AI from "tools" to "employees". In the first half of 2026, the number of financing events for Agent related startups increased by over 200% year-on-year.
From a regional distribution perspective, the AI entrepreneurship ecosystem in China is becoming increasingly mature. Beijing, Shanghai, Shenzhen, and Hangzhou are still the core cities for AI entrepreneurship, but emerging tech cities such as Chengdu, Nanjing, and Xi'an have also seen the emergence of a group of strong AI startups. Domestic capital tends to favor teams driven by both technology and scenarios, making it increasingly difficult to obtain financing for projects that are purely based on technology and do not understand the industry.
Looking ahead to the second half of the year, AI and embodied intelligence (humanoid robots), AI for Science (scientific intelligence), and AI security will become emerging investment directions worth paying attention to. For entrepreneurs, choosing the right track, delving into industry scenarios, and establishing sustainable business models are more crucial than chasing hot topics.