亚马逊中国副总裁邱胜：AI 正在改写跨境电商增长的底层逻辑

This article summarizes a speech by Qiu Sheng, Vice President of Amazon China, at the Global New Brands AI Competitiveness Conference. Its core insight is that AI has rewritten the underlying growth logic of cross-border e-commerce, bringing structural opportunities to the industry with clear actionable directions.

1. Current industry status: Over 300 million consumers globally already use Amazon AI shopping assistants, and conversion rates for AI-assisted shoppers are 60% higher than for non-users. More than 82% of Chinese sellers have integrated AI into their operations, with another 16% currently building AI-powered workflows. AI has evolved from an auxiliary tool to a core business partner for sellers.

2. Core application areas: AI has been deeply integrated across the entire cross-border e-commerce value chain, including product innovation, intelligent decision-making, operational automation, efficiency improvement and compliance & security. Mature Chinese seller use cases exist in every domain, which helps readers quickly understand practical AI applications in cross-border e-commerce and clarify the industry's development direction.

This article outlines AI-era brand positioning directions for global outbound brands, covering core dimensions brands care about most: consumer trends, product development, and operational growth.

1. Shifting consumer behavior: Shopping journeys have shortened dramatically, as consumers now directly describe their needs instead of actively searching for products. More than 300 million global consumers have adopted AI-assisted shopping, with a 60% higher conversion rate, and brands must adapt to this new consumer behavior.

2. Product development direction: Brands can leverage AI to uncover real user demand and shift from following hit products to defining new product categories with AI. For example, Hangzhou-based brand Merach used AI to transform traditional fitness equipment into smart connected trainers, increasing average user workout duration by 3.2x.

3. Operations and growth direction: AI can replace experience-based decision-making for product selection and pricing. After using AI to distill user demand, laser engraver brand xTool boosted its new product repeat purchase rate to over 40%. AI also enables proactive compliance risk prevention: Luyuan Technology achieved zero customs detention for its shipments via AI tools. Leveraging Amazon Global Selling, brands can launch globally from day one and capture global growth opportunities.

This article sorts out development opportunities, practical implementation paths, opportunity alerts, and available resource support for cross-border sellers in the AI era.

1. Industry opportunity assessment: Cross-border e-commerce is currently seeing AI-driven structural opportunities, as AI rewrites the underlying rules of growth. Sellers can transform from operators of repetitive tasks to global strategy decision-makers, significantly raising the industry's growth ceiling.

2. Practical implementation directions: AI needs to be integrated into five core links across the full value chain: using AI for consumer insights in product selection, replacing trial-and-error experience with data-driven decisions, automating operations to boost efficiency, solving labor efficiency bottlenecks for multi-market expansion, and enabling proactive compliance risk prevention. These methods have been validated by multiple mature seller cases and can be directly referenced and adopted.

3. Path selection and resource support: Sellers can choose a development path based on their own situation: established sellers can adopt a gradual upgrade approach, while new sellers can build an AI-native business from the start. Amazon is building a full-stack AI infrastructure to eliminate the need for sellers to explore AI applications independently, drastically lowering the barrier to AI adoption.

This article offers key insights on digital transformation, product upgrading and business expansion for manufacturing factories engaged in cross-border business.

1. Shifts in product design and demand: Consumers now describe specific needs instead of searching for pre-defined products. Factories can leverage AI to extract real user demand from massive datasets, shifting from the old model of copying trending hit products to independently defining new product categories to improve product competitiveness. For example, Merach captured user demand for workout companionship, transformed traditional fitness equipment into smart AI-powered trainers, and earned strong user feedback.

2. New business opportunities: AI has accelerated the "go global from day one" trend. Factories can leverage Amazon's cross-border supply chain system to quickly launch products to global markets, without building a complex in-house distribution network.

3. Insights for digital transformation: Factories do not need to complete a full digital transformation in one step. Traditional factories can take a gradual upgrade approach to integrate AI into production and operations step by step. New factories can build AI as a core foundational capability from the early startup stage to enable asset-light, rapid growth. AI also helps factories address labor efficiency and compliance challenges, enabling scalable growth without disproportionate increases in labor costs.

This article clarifies industry trends, core customer pain points, and new business opportunities for cross-border e-commerce service providers.

1. Industry development trend: AI has evolved from a point solution to a foundational capability that rewires the entire cross-border e-commerce value chain. The entire industry is shifting toward AI-driven global e-commerce, and seller demand for AI-related professional services will grow sharply, creating huge untapped market opportunities.

2. Core customer pain points: Today's sellers' top pain points include: lack of in-house AI application capabilities, inability to use AI for user insights and product selection, experience-based decision-making leading to inventory risks, insufficient labor efficiency for multi-market operations, and high-stakes cross-border compliance risks with low room for error. In addition, needs vary greatly by seller type: traditional sellers require gradual AI upgrade services, while AI-native sellers need full-stack AI workflow setup services.

3. Partnership opportunities: Amazon has publicly invited cross-border and AI-savvy service providers to join the Amazon Service Provider Network, building an ecosystem where the platform provides core AI infrastructure and service providers deliver professional, customized solutions. Service providers can acquire new customers through this ecosystem, deliver targeted solutions for sellers, and unlock new growth opportunities.

This article draws on a public speech by Amazon senior leadership, sharing development strategies for cross-border e-commerce platforms in the AI era that offer valuable references for operational positioning of all types of platforms.

1. Core merchant needs: Today, merchants' top demand from platforms is full-stack AI capability support across the entire value chain to lower the barrier to AI adoption, eliminating the need for merchants to invest heavily in building an end-to-end AI system in-house, while solving pain points across product selection, decision-making, operations and compliance.

2. Latest platform strategy: Amazon continues to make heavy AI investments, with a planned $200 billion in capital expenditure by 2026, most of which will go to AI. The company is building a full-stack AI infrastructure covering user insights, product selection, logistics, compliance and more, while partnering with service providers to build an ecosystem that meets the personalized needs of different sellers.

3. Operational direction and risk warning: Platforms need to support two types of merchants: serving the gradual AI upgrades of traditional merchants while welcoming AI-native new entrepreneurs. Platforms should also help merchants shift compliance risk management from post-incident remediation to proactive prevention, reducing operational risk for sellers. For platforms themselves, failing to proactively build AI capabilities will leave them unable to keep up with industry development and at risk of being phased out by the market.

This article reveals the latest development trends in the cross-border e-commerce industry, outlining new characteristics of AI-industry integration and emerging business models with high research value.

1. New industry trends: AI has completed its transformation from a point tool to a re-shaper of underlying growth logic, forming a new AI-driven paradigm for global e-commerce. On the demand side, consumers have shifted from active search to direct demand expression; on the supply side, sellers have transformed from operational executors to global strategy decision-makers. AI is now a core business partner for sellers, rather than an optional add-on.

2. Five core trends of industry restructuring: Product innovation has shifted from following hit products to AI-defined categories; business decision-making has shifted from experience-reliance to data-driven operations; operations have shifted from point tool adoption to end-to-end automation; efficiency improvement has shifted from headcount growth to AI-powered scalable growth; compliance and security have shifted from post-incident remediation to proactive risk management. These five interrelated trends are jointly restructuring the entire industrial value chain.

3. New business models and ecosystems: Two viable industry development paths have emerged: gradual upgrading for traditional merchants and AI-native development for new sellers. A new platform + service provider co-enablement ecosystem has also formed, where platforms provide core AI infrastructure and service providers deliver specialized capabilities to jointly serve different types of sellers. This represents an innovative direction for industrial ecosystem development.