JD Industrial (07618) participated in the Academy of Information and Communications Technology's Terminal Smart Ecosystem Co-construction Program to promote the implementation of industrial AI with smart devices

The Zhitong Finance App learned that the “From Big Models to Smart Devices: Towards a New Era of Autonomous Intelligence” forum, guided by the World Artificial Intelligence Conference Organizing Committee Office and hosted by the Chinese Academy of Information and Communications Technology, was successfully held in Shanghai on July 18. As one of the key forums on WAIC, experts from all walks of life conducted in-depth discussions on the evolution of smart technology, standardization construction, and industry implementation paths. At the forum site, the East China Branch of the Academy of Information and Communications Technology, in collaboration with the AI Computer Software and Hardware Adaptation Optimization Pilot Platform, officially released the “Shenzhi” terminal smart device evaluation platform, and simultaneously launched the terminal smart ecosystem co-construction plan. JD Industrial (07618) and ecological partners such as Lenovo Group, Huawei, Midea Group, Wuyuan Xinqiong, and Electronic Electronics Group jointly launched a platform to accelerate large-scale application and sustainable development of terminal smart devices, and work together to restructure a new standard for the smart terminal industry.

The 2026 “Report on the Work of the Government” clearly proposes “promoting the accelerated promotion of next-generation smart terminals and smart devices”. AI computers and mobile phones, AI glasses, physical intelligence, etc. have moved from concept to reality, and the industry's demand for capability classification and security management is becoming more and more urgent. As the first third-party neutral evaluation service platform for the next-generation smart terminal field in China, the “Shenzhi” terminal smart device evaluation platform fully integrates with the “Intelligent Classification of Artificial Intelligence Terminals” national standard, provides general evaluation services in the two dimensions of smart device safety and capability, drives the implementation of the evaluation system with real scenario requirements, provides the industry with a quantifiable and comparable scale, so that capacity improvement can be supported with evidence and rules to follow.

With large models as the core driving force, intelligent devices can sense the environment, independently plan, make decisions and execute actions, and achieve intelligent task processing across terminals, systems, and businesses, and have become the optimal carrier for enterprise AI applications. At the same time, enterprise-level intelligence is rapidly developing towards a trend from dialogue to execution, from individual soldiers to collaboration, from general to exclusive, and from project to ecology. Regardless of the number of agents, depth of application scenarios, or implemented value creation, they have made great strides.

Through the deep integration of real business data and vertical scenarios, artificial intelligence has “entered the factory floor” through intelligent devices and other methods, changing from “being able to test” to “understanding the business, being able to carry out tasks, and having results” to continuously optimize operational efficiency and transform commercial value. According to data, in the first quarter of 2026, JD Industrial continued to strengthen full-link AI technology capabilities, launched nearly 40 AI agents, and served more than 3,000 key enterprise customers. AI technology has now widely enabled product identification, intelligent matching and batch ordering, accurate forecasting of customer needs, and helped JD significantly improve human efficiency in core positions such as industrial procurement and product management.

For example, in the process of standardizing industrial product data, the first multi-agent platform “Work Product Inspection” to commercialize the full industrial product chain management can reduce the processing time for 100,000 grade products from “monthly level” to “hourly level”, increasing human efficiency by more than 10 times; 27 agents formed virtual teams, and labor costs were reduced by more than 80%. In the one-stop AI upgrade scenario in the mall, the procurement expert “AI shopping guide” becomes an intelligent shopping guide assistant that combines the knowledge of industry experts and big models, which can help customers reduce the time for model selection decisions by 70%, reduce the risk of mismatch and rework by 60%, and increase the order conversion rate by 48%. In the smart operation and maintenance scenario of the number of spare parts, the AI operation and maintenance expert “Jingbi Cloud” is an enterprise-specific remote expert team created by linking mobile terminals and cloud platforms, bringing about a 30% to 50% increase in quality inspection efficiency, a reduction in travel costs by more than 60%, an increase in quality problem interception rate by 40%, and an optimization of quality inspection labor costs by 25% to 35%.

The technical director of JD Industrial said, “In the next five years, JD Industrial will create a batch of high-quality, standardized, and recyclable industrial supply chain data sets to enable the full implementation of large-scale industrial models and intelligent devices, drive the industrial supply chain to reduce costs, increase efficiency, compliance and supply, and use technology to achieve the ultimate operational efficiency in the industrial world.”