AI Large Models Deepen Integration with Traditional Industries in China, Tackling Transformation Challenges
People’s Daily Online reports that artificial intelligence, represented by large models, is currently moving from the stage of single-point applications to in-depth integration with traditional industries in China. Exploring sustainable application models of AI in traditional sectors to systematically improve industrial efficiency and collaboration capacity has become an essential task for high-quality economic development.
Traditional industries serve as the mainstay of China’s national economy, the foundation of the real economy, and a crucial pillar for stabilizing growth, employment and prices. For a long time, traditional industries such as manufacturing have achieved rapid growth through factor input and scale expansion, but they also face prominent challenges including low efficiency, insufficient innovation and slow transformation.
Large models, with core capabilities such as deep learning, knowledge reasoning, cross-domain collaboration and autonomous optimization, can accurately address the pain points of traditional industrial transformation and promote a shift from factor-driven to innovation-driven development. China’s industrial practice has fully demonstrated the great effect of AI empowerment. In sectors such as iron and steel, textiles, energy and power, large models have been integrated into local technological processes and mastered industry-specific knowledge in various scenarios, including low-carbon safety, cost reduction and efficiency improvement, industrial collaboration, and accurate early warning and fault disposal, helping traditional industries break free from low-end lock-in and move up the value chain.
Xinhua News Agency notes that despite the remarkable progress, several bottlenecks still exist in the integration process. Data barriers remain prominent, with isolated data islands within enterprises and scattered industry data among different entities, while the supply of public data fails to meet demand. Many enterprises, especially small and medium-sized ones, are reluctant, afraid or unable to carry out digital transformation due to concerns about costs and risks. In addition, there is a severe shortage of interdisciplinary talents who understand both traditional industrial processes and AI technology, and some models are not closely integrated with industrial scenarios, with reliability and interpretability failing to meet the precision requirements of industrial production.
To address these challenges, a systematic and collaborative approach is required to build a development ecosystem guided by the government, led by enterprises, driven by the market and supported by multiple parties. China is taking a series of targeted measures to promote in-depth integration. Efforts are being made to integrate data resources, accelerate the formulation of industry data standards, and promote the classified opening and sharing of enterprise, industry and public data.
A vertical model supply system is also being constructed, with leading enterprises joining hands with research institutes and AI companies to build industry-specific large models focusing on iron and steel, chemicals, textiles and energy. Lightweight, low-cost and modular models are being promoted to adapt to the different digital foundations of small and medium-sized enterprises. Meanwhile, public service platforms for intelligent transformation are being built to provide one-stop services including technical consulting, testing and verification, and talent training.
Talent echelon construction is being strengthened through industry-education integration and school-enterprise cooperation, with universities and vocational colleges optimizing majors to cultivate interdisciplinary talents. Leading enterprises are playing a demonstration role, creating intelligent transformation benchmarks with in-depth application of large models and promoting replicable experience to drive small and medium-sized enterprises in the industrial chain to achieve full-link transformation. In the future, with the continuous advancement of these measures, large models will further empower traditional industries, helping China consolidate the foundation of the real economy and gain an advantage in industrial competition.
