AI Transforms Warehouse and Supply Chain Efficiency

AI Transforms Warehouse and Supply Chain Efficiency

Artificial Intelligence (AI) is profoundly transforming warehouse operations and supply chain management. This article explores AI applications in areas such as intelligent inventory management, automated picking, smart route optimization, demand forecasting, risk management, and supply chain optimization. Despite the challenges, AI will play an increasingly vital role in the future supply chain, helping companies gain a competitive edge. Its ability to analyze vast datasets and automate complex processes makes it a key enabler for efficiency and resilience in modern supply chains.

Agentic AI Transforms Retail Logistics Inventory Management

Agentic AI Transforms Retail Logistics Inventory Management

This paper explores the inventory management challenges faced by retail and logistics companies in omnichannel environments. It highlights how Agentic AI can improve inventory availability, optimize inventory health, increase operational efficiency, and reduce costs through intelligent demand forecasting, inventory optimization, and automated replenishment. The article also shares practical experiences from industry leaders and compares the advantages of Agentic AI over traditional inventory management systems, demonstrating its potential to revolutionize retail logistics and streamline inventory processes.

AI and Geopolitics Reshape 2026 Supply Chains

AI and Geopolitics Reshape 2026 Supply Chains

An ASCM report reveals that supply chains will face challenges from AI, geopolitics, workforce issues, and cybersecurity by 2026. Companies need to enhance AI application security, upskill employees, build diversified supply chains, embrace green logistics, and focus on macroeconomics and talent management. Strengthening resilience is crucial to thrive amidst change. Prioritizing cybersecurity measures and adapting to evolving geopolitical landscapes are also key for future success in the supply chain.

AI and Edge Computing Boost Logistics Efficiency

AI and Edge Computing Boost Logistics Efficiency

This webinar explores how AI vision and edge computing are reshaping the logistics industry. AI vision systems empower businesses to achieve intelligent transformation by optimizing workforce management, reducing loading and unloading times, improving operational efficiency, and enhancing customer service. Industry leaders will share practical case studies demonstrating how to rapidly deploy these solutions and gain real-time insights, helping logistics companies seize opportunities presented by technological change. Learn how to leverage these advancements for a competitive edge in the evolving landscape of logistics.

AI and Talent Shortages Reshape Logistics Industry

AI and Talent Shortages Reshape Logistics Industry

This paper delves into the challenges and opportunities facing the logistics industry, focusing on the impact of AI-driven digital transformation, technological innovation, talent strategy, and market trends on businesses. Through case studies, industry report analysis, and future outlook, it provides strategies for companies to respond to market changes and enhance competitiveness. The research emphasizes the importance of adapting to new technologies and cultivating a skilled workforce to thrive in the evolving logistics landscape. The paper aims to offer practical insights for businesses seeking to optimize their operations and maintain a competitive edge.

01/20/2026 Logistics
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AI Startup Ehisea Drives Digital Trade Expansion

AI Startup Ehisea Drives Digital Trade Expansion

Yihaichuangteng shared its AI-driven Brand Globalization 3.0 strategy at the 2025 Digital Trade Conference, emphasizing a shift from traffic acquisition to brand resonance. Addressing the opportunities and challenges in emerging markets, Yihaichuangteng helps Chinese companies build sustainable brand asset systems in overseas markets by constructing brand digital infrastructure and leveraging AI for marketing. This approach enables businesses to establish a strong brand presence and achieve long-term growth in the global landscape.

AI Search Tools Transform Manufacturing Customer Acquisition

AI Search Tools Transform Manufacturing Customer Acquisition

AI search optimization is crucial for manufacturing companies to acquire customers in the new era. Mico Network offers three core strategies: information structuring and reorganization, scenario-based content construction, and dynamic updates and maintenance. These strategies help companies translate their production strengths into AI-recognizable advantages, winning more business opportunities in the AI-driven procurement decision-making process and reshaping the factory customer acquisition model. By optimizing for AI, manufacturers can enhance visibility and attract more relevant leads, ultimately driving growth and success.

AI Boosts Crossborder Ecommerce in Emerging Markets

AI Boosts Crossborder Ecommerce in Emerging Markets

This week's cross-border e-commerce intelligence focuses on AI empowerment, lower-tier market opportunities, brand globalization strategies, and logistics supply chain integration. OpenAI's advertising initiatives and Google's AI shopping features indicate AI's deepening application in e-commerce. County-level and Latin American markets are emerging as new growth drivers. Brands like HEFANG Jewelry are accelerating their international expansion. J&T Express and SF Holding's mutual shareholding reflects new trends in the logistics industry. These developments highlight the dynamic landscape of cross-border e-commerce and the key strategies companies are employing to succeed.

Deepseek V4 Targets Global AI Programming Leadership

Deepseek V4 Targets Global AI Programming Leadership

DeepSeek plans to release V4 by Chinese New Year 2026, focusing on programming capabilities with the goal of surpassing Claude. V4 will feature enhanced code processing and reasoning abilities, leveraging technologies like Mixture of Experts (MoE). Pricing strategy is yet to be determined. The company is positioning this release as a significant advancement in AI programming capabilities, potentially setting a new benchmark for performance in code generation and understanding.

AI Models Boost Performance Via Imitation Learning

AI Models Boost Performance Via Imitation Learning

MIT research indicates that scientific AI models with different architectures converge on similar internal representations when addressing the same problem. Through model distillation, smaller models can mimic the representation logic of high-performance base models, achieving comparable prediction accuracy at a lower cost. Future evaluations of scientific AI will increasingly focus on whether models enter a "truth convergence circle." Lightweight, low-cost AI will accelerate scientific innovation by enabling efficient knowledge transfer and deployment of effective solutions.