The Dragon Algorithm: China’s Conquest of the LLM Market
The Dragon Algorithm: China’s Conquest of the LLM Market
https://www.startupbusiness.it/en/the-dragon-algorithm-chinas-conquest-of-the-llm-market/164650/
Publish Date: 2026-04-24 03:00:00
Source Domain: www.startupbusiness.it
The prevailing assumption in artificial intelligence strategy is, on the surface, disarmingly simple: the organisations that are first to reach a critical mass of adoption will prevail. Lower costs, rapid uptake among developers and data feedback loops create a self-reinforcing dynamic in which usage generates data, data improves models, and improved models attract further users.
At first glance, recent evidence appears to confirm this logic. Global usage of large language models rose from around 2.4 billion to over 8 billion monthly visits between April 2024 and August 2025 — a 3.4-fold increase in sixteen months (Wang & Siler-Evans, 2026)[1]. During the same period, Chinese models gained market share at an unprecedented rate: from 3% to 13% of global usage within two months of the release of DeepSeek R1 (Wang & Siler-Evans, 2026)[1].
Yet this interpretation, however convincing, is incomplete. It explains how artificial intelligence spreads, but not how value is captured or defended over time. What is missing is the structural level underlying adoption: the geography of production, the distribution of capital and the configuration of the AI value chain (Agostini, 2025a; Agostini, 2025b)[2,3].
The competitive advantage in AI does not stem from the performance of a single model, but from control over the systems that enable its production, distribution and scalability.
A closer examination of the data reveals a more complex and asymmetrical picture. Chinese labs are gaining ground in the infrastructure and open-model layers of the LLM ecosystem, whilst US companies continue to dominate the enterprise and application layers. This is not a temporary divergence, but the result of profound structural differences in the way the two ecosystems are built and scaled.
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