In 2026, Capital Prices AI Companies Along Industrial Clusters

As 2026 passes its midpoint, China's AI investment market is undergoing a quiet yet profound paradigm shift. The old investment logic of casting wide nets on star teams and hot tracks is being replaced by a more structurally minded pricing approach — capital has begun pricing AI companies 'along industrial clusters.'

An increasingly clear picture is emerging: the north, centered on Beijing, has formed a 'models + applications' industrial cluster; the south, anchored by Shenzhen, Dongguan, and the Yangtze River Delta, has built a manufacturing-oriented AI ecosystem around 'embodied intelligence + hardware.' This geographic industrial differentiation is redefining the valuation coordinate system for AI companies.

The Shift in Investment Logic: From 'Betting on Teams' to 'Evaluating Clusters'

Looking back at the AI investment boom from 2023 to 2024, the core logic of capital was 'betting on people.' Whichever big-tech executive left to start a company, whichever lab published a breakthrough paper, money would flood in. This logic spawned a large number of overvalued AI startups and created considerable bubbles.

Entering 2026, after a round of industry shakeout, the surviving investment institutions have begun adopting a fundamentally different evaluation framework. Multiple frontline investors have expressed similar views in recent industry exchanges: evaluating a single AI company in isolation no longer makes sense — it must be assessed within the context of its surrounding industrial cluster.

The core logic of 'pricing along industrial clusters' is this: an AI company's value depends not only on its own technology and products, but even more on the maturity, synergistic efficiency, and growth potential of the upstream and downstream ecosystem in which it is embedded. In other words, capital no longer pays for isolated technology, but for 'node value' within an entire industrial network.

Three key driving forces underpin this transformation:

First, the commercialization of AI technology itself has entered deep waters. The pure model capability race has reached a stage of diminishing marginal returns, and deployment scenarios and industrial support infrastructure have become the key factors determining commercial value.

Second, local government industrial policies continue to shape cluster effects. Different regions have developed differentiated AI industry positioning in their investment attraction efforts, and the compounding effect of policy dividends has given companies within clusters significant cost and resource advantages.

Third, localized supply chain synergy has been proven to be the core moat for AI hardware startups. Especially in the embodied intelligence space, the closer a company is to its supply chain, the faster it can iterate and the stronger its cost control.

The Northern Cluster: A Software Ecosystem of 'Models + Applications'

The northern AI cluster, with Beijing as its absolute center, exhibits a distinct 'software DNA.' It concentrates China's top large language model companies, the densest community of AI application developers, and the most active enterprise AI services market.

Beijing's advantages are rooted in its unique resource endowment: top universities and research institutions provide a continuous stream of algorithm talent, the spillover effect from internet giants has cultivated mature engineering capabilities, and the concentration of central government ministries and large state-owned enterprises provides natural demand-side support for To-B and To-G AI applications.

At the model layer, Beijing is home to leading large model companies such as Zhipu AI, Baichuan Intelligence, and Moonshot AI, which continue to deepen their work in both general-purpose and industry-vertical models. By 2026, the valuation logic for these companies has shifted from 'parameter scale' to 'API call volume and revenue growth rate,' with capital paying more attention to the efficiency of converting model capabilities into actual revenue.

At the application layer, Beijing has seen a surge of vertical application companies built on large models, covering fields such as law, finance, healthcare, education, and government affairs. These companies share a common characteristic: leveraging the mature model infrastructure within the northern cluster to rapidly build scenario-specific products with relatively low technical barriers, while using geographic advantages to secure major client contracts.

The capital pricing logic for the northern cluster can be summarized as follows: Model companies are evaluated on 'platformization potential,' application companies on 'scenario penetration rate and customer stickiness,' and the synergy between the two determines the overall valuation ceiling of the cluster.

Notably, the northern cluster also faces challenges. Homogeneous competition at the model layer remains intense, willingness to pay and renewal rates at the application layer still need validation, and the value distribution tug-of-war between 'models' and 'applications' continues. Some investors candidly acknowledge that application companies in the northern cluster face the risk of 'being disrupted by model companies' — when large model companies enter the application space themselves, pure application-layer companies may see their moats erode rapidly.

The Southern Cluster: Manufacturing-Oriented AI of 'Embodied Intelligence + Hardware'

In stark contrast to the north's software ecosystem, the southern AI cluster has forged a 'hardcore' path. The Greater Bay Area centered on Shenzhen and Dongguan, along with the Yangtze River Delta region anchored by Shanghai, Suzhou, and Hangzhou, is becoming a global manufacturing hub for embodied intelligence and AI hardware.

The core competitiveness of the southern cluster lies in its unparalleled hardware supply chain advantages. Shenzhen and its surrounding areas boast the world's most complete electronic component supply chain, the most efficient small-batch rapid prototyping capabilities, and the most cost-competitive manufacturing systems. As embodied intelligence moves from the lab to productization, these capabilities become the decisive factors in determining winners and losers.

In 2026, embodied intelligence companies in the southern cluster exhibit a clear tiered structure:

The first tier consists of humanoid robot and industrial robot companies with full-stack capabilities, with deployments across algorithms, hardware, and scenario implementation. Their valuations are generally in the billions of yuan.

The second tier comprises companies focused on core components, including specialized firms in sub-segments such as dexterous hands, joint modules, torque sensors, and visuo-tactile sensors. While these companies are not large in scale, they are attracting intensive capital attention because they occupy critical nodes in the supply chain.

The third tier includes peripheral ecosystem companies for AI hardware, covering simulation platforms, data collection equipment, testing tools, and more. They provide infrastructure support for the entire embodied intelligence industry.

The capital pricing logic for the southern cluster is: System integrators are evaluated on 'mass production capability and order pipeline,' component companies on 'technological moats and customer coverage,' and the valuation anchor for the entire cluster is the global industrialization progress of embodied intelligence.

The southern cluster's unique advantage is that it inherently possesses 'global expansion DNA.' Shenzhen's hardware companies have been oriented toward global markets from day one, giving companies in the southern AI cluster more experience and channel advantages in overseas market expansion compared to their northern counterparts. In the current international environment, the global deployment of AI hardware has become a valuation premium.

Competition, Cooperation, and Convergence Between Clusters

The two major clusters in the north and south are not entirely separate; they are experiencing increasingly frequent interaction and convergence.

The most typical case is that northern large model companies are establishing deep partnerships with southern embodied intelligence companies. The general reasoning capabilities and multimodal understanding provided by large models are becoming the 'brain' of embodied intelligence systems, while the south's hardware platforms provide large models with interaction interfaces to the physical world. This cross-cluster synergy is creating new value spaces.

At the same time, some companies have begun adopting a 'dual headquarters' strategy — placing R&D and algorithm teams in Beijing, while locating hardware and manufacturing teams in Shenzhen or the Yangtze River Delta. This layout itself represents an active adaptation to industrial cluster logic.

Capital is also adjusting its own deployment strategies. Some leading funds have begun establishing dedicated 'cluster investment portfolios,' systematically investing in upstream and downstream companies within the same industrial cluster and using post-investment management to promote synergies among portfolio companies, thereby enhancing the value of the entire portfolio. This investment approach is not uncommon in traditional manufacturing investment, but it represents a new trend in the AI space.

The Deeper Transformation in Pricing Methodology

'Pricing along industrial clusters' is not merely an adjustment in investment strategy,