Workflow
对话万联易达副总裁:产业AI应用将变成新型基础设施
Guan Cha Zhe Wang·2025-07-31 07:53

Core Insights - The article highlights the emergence of artificial intelligence (AI) as a transformative force in various industries, with 2025 being identified as a pivotal year for AI breakthroughs [1] - Wanlian Yida Group is positioned as a benchmark enterprise in the integration of AI with the industrial internet, focusing on creating a comprehensive AI solution that spans over 90 industries [1][2] Company Overview - Wanlian Yida was established in 2018 and has evolved from a traditional logistics service provider to an integrated industrial internet ecosystem operator, encompassing AI applications, commodity trading, logistics, and financial services [1][4] - The company aims to build a new industrial internet ecosystem with four main components: AI applications, commodity trading, logistics, and financial services [4][5][6] AI Strategy - The company emphasizes that its AI initiatives are not merely about applying technology to industry but about enabling AI to understand industrial logic and improve response accuracy to industry-specific challenges [2][7] - Wanlian Yida is developing a comprehensive industrial model that will cover over 90 industries, focusing on enhancing operational efficiency and quality for various enterprises [7][8] Data and Decision-Making - The core of the comprehensive industrial model is to shift from experience-driven to data-driven decision-making, thereby unlocking efficiency across the entire supply chain [8][9] - The model will utilize real-time data from various sources, including supply chain and production data, to provide actionable insights for businesses [8][9] Future Trends - The future of industrial AI is expected to evolve from single-point optimization to holistic collaboration across the entire supply chain [11] - There is a shift from data-driven approaches to intelligent decision-making, with AI moving towards autonomous decision-making capabilities [11][12] - The development of industrial AI is being driven by both policy support and market demand for cost reduction and efficiency improvement [12]