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This article outlines that all major Chinese e-commerce platforms have rolled out AI-powered shopping tools recently, with Kuaishou officially launching its AI shopping assistant and upgrading merchant support policies to capture market share in the AI e-commerce sector. General consumers can find the following key takeaways:

1. Kuaishou’s newly launched AI shopping assistant features a simplified user flow: after searching for a product, users can enter the tool to submit their needs via text conversation, such as sharing their budget and product preferences. The system will directly generate product cards with built-in shopping carts, allowing users to add items to cart without redirecting to product detail pages. After-sales benefits are also clearly displayed, significantly cutting down product selection time.

2. The function is currently only available in search scenarios, and has not yet covered Kuaishou’s core live streaming and short-form video e-commerce scenarios, with full rollout planned for the future.

3. Alibaba, Douyin, JD.com and Pinduoduo have all launched AI shopping tools in different forms. Users can test AI-powered导购 services across platforms to speed up product selection and improve shopping efficiency with AI assistance.

AI e-commerce has become a core competitive direction for the industry, with all major platforms ramping up investments. Brands can take away the following key insights:

1. Consumer trend perspective: AI导购 is reshaping user shopping habits. Conversational product selection and streamlined one-click checkout are growing in popularity, and shortening user decision paths has become an industry-wide priority. AI also makes user demand more transparent, helping brands adjust their product strategies.

2. Channel opportunity perspective: Kuaishou has upgraded its Q3 Xingyao Program. New brand merchants can stack three benefits: GMV rebates, ad flow subsidies, and growth incentives. They also get free access to AI-powered business tools including one-click product listing and smart live streaming. The 0-deposit trial operation has been expanded to include reopened stores, and a single business license can now register up to 5 trial stores, drastically lowering entry barriers.

3. Layout recommendation: AI e-commerce is still in its early stages, and user habits have not yet solidified. Kuaishou is exploring a differentiated "AI + trust e-commerce" model. Brands can enter this new Kuaishou channel early, while focusing on improving fulfillment services to boost user retention.

AI e-commerce is a new high-growth track, and all major platforms have rolled out new support policies. Sellers can review the following opportunities, risks and operational guidance:

1. Latest policy breakdown: Kuaishou has upgraded its Q3 Xingyao support program. The 0-deposit trial operation has been extended from brand-new stores to reopened stores, allowing up to 5 trial stores per business license. Both the tiers and amounts of growth incentives have been increased. New merchants can access three layers of incentives, plus free AI-powered operation tools covering product listing, live streaming and short-form video management to reduce operational friction. This support package already covers more than 1 million merchants.

2. Opportunity note: AI e-commerce is still in early adoption, with user habits not yet fully set. Kuaishou is rapidly building out its AI capabilities and competing aggressively for merchant and product supply. Entering early means access to the platform’s traffic subsidies. Data from the first half of 2024 shows that participating new merchants saw an average nearly 15% increase in full-domain GMV from ad spending, proving the model works.

3. Risk note: While all major platforms offer large subsidies currently, long-term profitability and user retention are the core goals beyond short-term incentives. Kuaishou still has weaknesses in SKU diversity, logistics and after-sales services. Sellers need to prioritize high-quality fulfillment, keep up with the expansion of AI functional scenarios, and adapt to new platform rules early.

The growth of AI e-commerce has opened new business opportunities for factories and outlined a clear direction for digital transformation. Key insights are as follows:

1. Product development and design reference: AI导购 can quickly aggregate user personalized demand including budget, style and functional preferences. Factories can use the AI-collected demand data provided by platforms to adjust production and design directions to better match real consumer needs, increasing the chance of developing hit products.

2. Business opportunities: All major platforms are competing for merchants and product supply. Kuaishou’s Xingyao Program drastically lowers entry barriers for stores and offers free AI operation tools. Factories can build a direct-to-consumer sales channel on Kuaishou, cutting out middlemen and increasing profit margins.

3. Digital transformation takeaways: AI has become a core technological variable for the e-commerce industry. For factories pursuing digital and e-commerce transformation, it is critical to follow AI industry trends, proactively adopt AI tools provided by platforms to reduce operational complexity, capitalize on the early window of AI e-commerce to build market presence, and continuously improve supply chain and fulfillment capabilities to deliver better user experiences and retain customers long-term.

AI e-commerce is in the early stage of rapid growth, bringing new industry trends and new service demand. Key insights are as follows:

1. Industry development trends: AI shopping assistants have become a standard feature for all major Chinese e-commerce platforms. Industry competition has shifted from "having the feature" to "how well it works and how much it boosts conversion rates". AI is重构 the entire e-commerce value chain from product recommendation to order fulfillment. C-end AI导购 and B-end AI operation tools are the two core areas of implementation. Going forward, building differentiation by combining AI with a platform’s existing unique strengths will become the mainstream approach — for example, Kuaishou is exploring an AI + trust e-commerce model.

2. Key pain points: On the user side, the core pain point is long product selection decision paths and low shopping efficiency. On the merchant side, especially for new merchants, pain points include high store setup costs and a lack of efficient operation tools. On the platform side, pain points include weak AI product performance, low in-platform conversion rates, and failed transaction retention as users often complete purchases on other platforms after discovering products here.

3. Solution reference: The current industry standard approach is embedding conversational AI导购 on the C-end to shorten decision paths, providing free AI tools on the B-end to lower operational barriers, and attracting merchants with deposit waivers and traffic subsidies. Service providers can develop AI tools tailored for different transaction scenarios that address the pain points of platforms, merchants and users to capture industry growth opportunities.

As competition in AI e-commerce intensifies, the layout choices and challenges of leading platforms offer valuable reference for other e-commerce platform operators. Key insights are as follows:

1. Market demand: The core user demand for platforms is a more efficient and convenient shopping experience with shorter decision-making paths. For merchants, core demands include lower store setup costs, practical operation tools, and sufficient traffic incentives to achieve sustainable profitability.

2. Latest industry practices: All major mainstream platforms have completed basic AI layout. Alibaba has integrated its Qianwen large language model across the entire transaction chain; ByteDance has placed Doubao’s "Help Me Choose" in its primary navigation; JD.com has opened its AI capabilities to the external ecosystem; Pinduoduo has embedded AI into its core transaction processes; Kuaishou, meanwhile, has launched its AI shopping assistant and upgraded merchant support to compete for product supply.

3. Operations and management reference: The entire industry is competing for merchants and product supply, so attracting sellers by lowering entry barriers, increasing incentive amounts, and offering free AI tools is an effective go-to-market strategy. Beyond short-term subsidies, platforms must help merchants achieve sustained profitability to drive long-term retention. Platforms also need to quickly expand AI coverage to core transaction scenarios including live streaming and short-form videos to build a user growth flywheel, and continuously improve e-commerce ecosystem weaknesses such as SKU diversity, logistics and after-sales services to boost fulfillment experiences and retain users.

AI e-commerce is the most important new development in the current e-commerce industry, bringing many new industry characteristics and research questions. Key research insights are as follows:

1. New industry trends: Large AI models are reshaping the competitive landscape of the e-commerce industry. All major mainstream platforms have completed basic layout of AI shopping tools, and this year’s 618 Grand Promotion became the industry’s first AI-native major shopping festival. Competition has shifted from initial feature coverage to performance competition. Overall, AI e-commerce is still in the early penetration stage, with user habits not yet fully solidified, and all platforms are racing to secure market position.

2. New industry challenges: Late-moving platforms face multiple layers of growth pressure. The overall mobile internet user market has peaked, so platforms must prevent user分流 in a saturated competitive environment. Late-moving platforms also lag behind leading platforms in C-end AI product awareness, lack AI coverage in core transaction scenarios, have weaker foundational e-commerce ecosystems with shortcomings in SKU diversity, logistics and after-sales services, and commonly face the problem of users completing purchases on other platforms after discovering products here.

3. New business model exploration: The industry has seen a new exploratory direction of "AI + trust e-commerce". Kuaishou’s strategy is to launch AI导购 on the C-end to shorten decision paths and retain transactions, while increasing B-end support to attract merchants and product supply. It plans to leverage the platform’s existing community trust relationships to build a differentiated user experience. This new model for late-moving platforms to compete in the AI e-commerce track provides a new research sample for the industry, and its future development warrants continued close observation and research.