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环球产业对话:价格内卷成为过去式 AI正让中国工厂靠“可靠”赚钱
Huan Qiu Wang Zi Xun· 2026-01-17 06:31
Core Insights - The article highlights the transformation of Chinese manufacturing businesses, driven by AI technology, leading to a shift from traditional models to user-centered, AI-driven operations [3][5][10] Current Development Status - The recovery of the industrial sector is characterized as a "K-shaped recovery," where 20%-30% of leading businesses experience significant growth in orders and profits, while others relying on traditional methods face ongoing pressure [3][4] - Compliance and AI have become dual-edged swords for survival, with rising operational costs and market pressures reshaping business dynamics [5][6] Structural Shifts - AI has triggered three major structural shifts: 1. Decision-making mechanisms have evolved from intuition-based to data-driven models using AI [6] 2. Organizational structures are transitioning from linear processes to AI-driven coordination [6] 3. Core competencies are shifting from traditional skills to the ability to rapidly adapt AI models [6] Trends Under AI Influence - The order model is shifting from a "push" to a "pull" system, with businesses increasingly responding to end-user demand through AI [7][8] - The competitive landscape is evolving, focusing on product quality, service reliability, and certainty rather than just price [8][10] Driving Factors - The practical application and platformization of AI technology are key drivers of this transformation, with significant increases in visitor engagement and transaction volumes reported [10] - The role of platforms is changing from mere traffic operators to ecosystem builders, fostering collaboration with quality manufacturers [10][11] Future Directions - The future of Chinese industrial sectors will be significantly influenced by AI, with a transition from "product export" to "capacity export" and "flexible export" strategies [13] - The evolution of AI will progress through three phases: "AI as a tool," "AI in collaboration," and "AI as a core component," enhancing operational efficiency and decision-making [12][13]