On January 15th, a significant event in the realm of logistics and supply chain management took place: the China Supply Chain and Logistics Technology Innovation Conference was successfully held, hosted by the Rogow Network and Logistics SalonThe conference featured discussions about the transformative impact of Artificial Intelligence (AI) on supply chains, led by Wan Cheng, the Product Ecosystem Director of a notable logistics company, Zhuntimda.

The advancements in AI technology have become a global sensation, rapidly evolving from deep learning models to automation in decision-making processesThe intricate complexities and uncertainties inherent in supply chain operations have positioned AI as a crucial tool in this fieldCurrent trends have the industry exploring how AI can enhance supply chain capabilities, leading to more efficient and effective operations.

AI is increasingly becoming a linchpin in modern supply chain management, addressing the growing complexities businesses face today

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Traditional approaches to supply chain management are proving inadequate to meet the needs of contemporary enterprises, leading to a search for innovative solutions afforded by AI.

According to Gartner's report on the top ten trends in supply chain for 2025, AI is at the forefront, accompanied by factors such as geopolitical influences, data analytics, and visibility into supply chain risk managementAI’s capacity to redefine operational boundaries presents supply chain managers with unparalleled opportunities to innovate and enhance their practices.

The applicability of AI spans across all stages of the supply chainAn effective supply chain entails a closed-loop system that encompasses multiple processes—from demand forecasting to deliveryThe power of AI lies in its ability to permeate each segment, facilitating optimization and enhancement throughout.

At the planning and forecasting stages, AI's capabilities enable businesses to predict demand fluctuations with high accuracy, thus formulating more scientific production and procurement plans

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For instance, in the retail sector, AI can forecast which products might become bestsellers, allowing businesses to stock up in advance and avoiding the pitfalls of inaccurate predictions, which could lead to overstocking or stockouts.

In the logistics domain—one of the more complex aspects of the supply chain, especially concerning international trade—AI can analyze real-time transportation data, estimate congestion levels at ports, and stay updated on import/export regulations, all of which guide enterprises in planning the most efficient shipping routesZhuntimda, for example, has successfully integrated AI to optimize cross-border transportation, shortening delivery times and significantly reducing logistics expenses.

Furthermore, in production and manufacturing, AI can integrate real-time data on order demands, equipment status, and raw material inventories to dynamically adjust production schedules, thereby preventing capacity wastage

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In inventory management, AI algorithms can facilitate real-time adjustments, ensuring that stock levels are maintained efficiently without overstocking.

Moreover, AI can play a pivotal role in supply chain network designBy simulating various scenarios, AI helps businesses identify the optimal network structure, including warehouse locations, factory placements, and transportation route planningIn terms of operational efficiency, AI identifies bottlenecks in processes and promotes automation, thereby minimizing human intervention.

These examples underscore how AI is comprehensively reshaping supply chain managementNot only does it contribute to smarter supply chains, but it also empowers businesses to gain a competitive edge within the market.

In recent years, the international supply chain landscape has significantly shifted due to geopolitical factors and the reconfiguration of global supply chains from centralized to more complex, decentralized regional networks

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This transformation has introduced substantial challenges, such as extended supply chain links and increased complexity in nodes, coupled with unexpected events that create uncontrollable demand-supply dynamics and cost uncertainties.

To tackle these challenges, companies are in need of innovative solutions, with AI emerging as a powerful disruptorAI empowers supply chains by offering new strategies that enhance visibility across the entire chain, precision in demand forecasting, and improved resilience within supply networks—all of which contribute to building smarter and more agile supply chains.

Zhuntimda's innovative JusLink digital supply chain management platform exemplifies this advancementThe JusLink platform, driven by AI, functions as a control tower that encompasses data integration, management, and algorithmic modeling across all supply chain stages—from suppliers to customers, and from raw materials to finished goods

This facilitates holistic supply chain management by enabling real-time data collection and analysis, which supports seamless transitions from forecasting to decision-making.

JusLink's control tower houses three core modules—planning, procurement, and logistics—integrated with data algorithms and models, delivering efficient and intelligent supply chain management solutionsThe planning module focuses on inventory optimization and replenishment strategies through accurate demand predictionsOnce precise supply chain plans are established, AI algorithms help anticipate market demands and optimize inventory levels to reduce overall supply chain costs.

The procurement control tower utilizes clustering and anomaly detection algorithms to refine purchasing strategies, enhancing procurement efficiencyIn logistics, JusLink monitors transportation status in real-time, employing AI algorithms for anomaly alerts and rapid proposal generation for optimal solutions

After consolidating comprehensive logistics data, customs information, and transaction orders, JusLink can propose the most effective logistics strategies and respond swiftly to unforeseen logistics issues.

For increased efficiency, the JusLink platform incorporates a powerful AI assistant—JusAI—that simplifies complex supply chain operations through conversational interfacesBy merely instructing JusAI about demands, users can seamlessly manage tasks like searching for warehouse capacity, booking routes, and even creating replenishment plansThis revolutionary approach to logistics streamlines supply chain management, alleviating user workloads significantly.

The JusLink control tower also excels in risk management within the supply chain contextSupply chain risks are omnipresent—from natural disasters to geopolitical instabilities—and each poses significant challenges to the stability and efficiency of supply chains.

JusLink has distinguished itself in risk management by incorporating external data sources to capture and analyze relevant global events proactively

The platform continuously aggregates significant data points and merges them with operational information, producing timely alerts and insights regarding potential risksAI models actively analyze recognized risks against operational data, enabling precise identification and analysis of their potential impacts on ongoing operations.

One of JusLink’s notable features is its dynamic Estimated Time of Arrival (ETA) algorithmBy employing real-time tracking of vessel positions alongside weather data, this algorithm promptly warns of logistical anomalies and helps businesses adjust their logistics plans dynamically to mitigate the risks of supply chain disruptions.

Another critical area where JusLink shines is in its demand forecasting and dynamic inventory optimization capabilitiesThe intelligent demand forecasting module utilizes advanced algorithms to deliver accurate sales forecasts based on sales patterns and business contexts

The platform's flexibility allows it to adjust forecasting parameters dynamically, accommodating various scenarios, such as new product launches or seasonal variations in consumer demand.

JusLink's robust algorithm library includes both traditional statistical models and advanced deep learning models (like Deep-AR and TFT), ensuring refined outputs for sales forecasting that not only enhance accuracy but also provide substantial backing for inventory management, production planning, and replenishment strategies.

The dynamic inventory optimization feature capitalizes on preliminary demand forecasts, empowering users to manage inventory more precisely and efficientlyBy considering multiple inventory layers and coordinating replenishment strategies, JusLink enhances service levels while optimizing overall supply chain costsThe intelligent algorithms evaluate various cost parameters to generate replenishment strategies that minimize shortages while optimizing order quantities.

For instance, one client utilizing JusLink reported a remarkable 23% reduction in overall inventory levels following the implementation of tailored demand forecasting and replenishment strategies.

In conclusion, in an era characterized by uncertainty, supply chain resilience and agility have become core competitive components for businesses