Nanjing Iron & Steel Co., Ltd. (NISCO), in collaboration with Huawei and ecosystem partners, has commercially deployed the world's first steel model powered by swarm intelligence—the YuanYe Steel Large Model—across multiple scenarios at scale. The announcement, distributed via Media OutReach Newswire, signals a significant step in the steel industry's transition from experience-based operations to data- and intelligence-driven production. For a traditional manufacturer facing mounting pressure to transform and cut costs, the move matters because it demonstrates that AI can be embedded into every core stage of steelmaking—ironmaking, steelmaking, rolling, and quality inspection—at industrial scale, not just in pilot projects.
Unlike general-purpose monolithic models, YuanYe fuses multiple AI models with metallurgical mechanism models to create a dual-drive, multi-model cluster architecture. This "right brain" for probabilistic computing and "left brain" for precise decision-making draws on massive sensing data from millions of operational technology data points across 26 business domains. The result is a real-time digital twin within NISCO's intelligent operations center, making the entire steelmaking process visible, precisely controllable, and intelligently assessable. The implications are concrete: 100% of key equipment is now connected and digitally controlled, new product R&D cycles have been shortened by 50%, and annual costs have been reduced by over CNY100 million (approximately US$15 million).
The scale of deployment is equally notable. By October 2026, NISCO had launched 25 business agents covering visual quality inspection, process optimization, production scheduling, and operations management, alongside more than 300 AI models and over 1,000 low-code agents built independently by frontline employees. This breadth suggests that the value of industrial AI lies not in isolated applications but in comprehensive integration with production, operations, and management—a point emphasized by Cheng Yongfu, Senior Industrial Solution Expert at Huawei's Steel & Non-ferrous BU, who noted that sustained, scalable empowerment only emerges when AI expands beyond single-point uses.
Breakthroughs in four core scenarios illustrate why this matters for the wider industry. In ironmaking, AI makes blast furnaces transparent, predicting temperatures and identifying issues two hours in advance with over 90% accuracy, increasing prime-grade molten iron yield by over 10% while cutting unit energy consumption. In rolling, a millisecond-level rolling-force prediction model narrows thickness tolerance to ±0.2 mm and reduces thickness deviation to 1.9%, raising the rolling-force hit rate from 88% to 98% and supporting annual output of over 2.5 million tons of steel plates. In quality inspection, an integrated smart metallographic system doubles efficiency, lifting accuracy above 95% and cutting per-sample inspection time from 10 minutes to 3–5 minutes. In energy and environmental control, the S-Link Intelligent Agent for Gas and Flue Gas Sulfur Control issues sulfur-risk warnings an hour in advance with over 95% accuracy, slashing natural gas co-firing consumption by nearly 50% and reducing emission-related downtime by over 25%.
Beyond operational metrics, NISCO frames the transformation as human-centric. Li Jinyan, General Manager of the Digital and Intelligent Integrated Development Department and Director of the AI Research Institute at NISCO, said the purpose is not to replace people but to unleash human potential, lifting employees out of the endless sea of data so they can direct creative energy toward higher-value work. Looking ahead, NISCO plans to explore dedicated data centers for smart steel plants built on an AI-native three-tier architecture, aiming to provide a replicable and scalable benchmark for the digital and intelligent transformation of the global steel and manufacturing industries.
