AI开始懂经营，京东正在重做商家的生意系统

The core takeaway is that e-commerce AI is evolving from a pure efficiency tool into a business-savvy assistant that can understand a merchant and support decision-making. Using JD.com as an example, the article shows how AI helps merchants achieve intelligent, full-chain operations.

1. JD.com launched the Jingmai AI Operations Center, integrating five modules — Super Assistant, AI Experts, and Full-Chain AI Diagnosis — with more than 60 AI tools covering store operations, opportunity-driven product selection, product content, marketing, order fulfillment, and customer service. Merchants can ask questions in natural language, and AI can complete complex operations such as batch processing, automated inspection, and intelligent store setup.

2. The value of AI lies in giving results, not just tools. For example, the AI Design Expert only requires merchants to submit product information and business goals, after which it generates content and connects the advertising pipeline. One merchant in the health-appliance category saw the transaction value of product detail pages grow by more than 20% month over month after 14 days of use. AI can also scan a store across multiple dimensions, locate operational weaknesses, and deliver actionable optimization suggestions.

3. For ordinary merchants, AI means low-cost access to professional operating capabilities. More than 1.5 million merchants have used Jingmai AI tools, and daily active users have surpassed 500,000. JD.com also offers new merchants one-click advertising activation and a 200-yuan advertising bonus. In addition, AI shopping assistants are changing user behavior from proactive search to direct questioning, and merchants need to watch for exposure and conversion opportunities in this new arena.

The core insight for brands is that the AI operating paradigm is reshaping brand-platform collaboration: brands provide knowledge and strategy, while the platform provides data and AI capabilities, and both sides co-create a new operating model.

1. Brand marketing: AI shopping assistants are shifting consumers' purchase journey from searching to asking. JD.com's upgraded AI Product Operations Center, built around the three standards of completeness, accuracy, and quality, helps brands solve the pain points of consumers being unable to find products, understand descriptions, or trust products. This improves product exposure, clicks, and product-detail-page conversion, giving brands a new lever for marketing in the AI-driven arena.

2. User behavior observation: The article reveals a shift in shopping habits — more users are moving from proactive search to direct questions. Brands should adapt to this trend, using AI tools to understand the needs behind consumers' questions and optimize product information and content.

3. Product R&D and channel building: JD.com adopts a platform + service provider + brand merchant tri-party co-creation model, allowing brands to participate deeply in AI tool development. For example, P&G is exploring with JD.com how to integrate brand operating experience with AI capabilities and embed AI into business processes. Lenovo also said that AI is moving from helping with execution to helping with judgment, and expects AI to truly understand business operations. Brands should seize the opportunity to turn their operational knowledge into AI-ready strategies and achieve predictable incremental growth.

4. Price competition: Although the article does not directly discuss pricing, it notes that AI can aggregate consumer data and provide full-chain capabilities from demand mining to AI-launched managed operations. This helps brands match demand more accurately and optimize product strategy, indirectly affecting pricing and competitive efficiency.

The core value for sellers is that JD.com is using AI to help merchants move from knowing how to do things to understanding how to run a business, supported by a series of tools, policies, and new models that sellers can use for predictable growth.

1. Policies and support: JD.com released four major upgrades: a platform value proposition, synergy between first-party and POP businesses, increased support investment, and a better business environment. At the upcoming JD.com 11.11, JD.com will increase AI tool investment and drive the number of new merchants with sales over 1 million yuan to grow by more than 60% year over year. New merchants can also receive one-click advertising capability and a 200-yuan advertising bonus.

2. Growth markets and changing consumer demand: AI shopping assistants are reshaping the online shopping experience; users are shifting from proactive search to direct questions. Sellers need to re-understand consumer demand and use the AI Product Operations Center to address the pain points of consumers not finding products, not understanding descriptions, and not trusting products. Around the standards of completeness, accuracy, and quality, sellers can improve product exposure, clicks, and conversion.

3. Risk and response: The article points out the common merchant pain points of too many tools, difficult adoption, heavy operations, and insufficient manpower. JD.com is therefore upgrading from giving tools to giving results, launching AI expert teams for advertising, products, product selection, customer service, membership, and other scenarios. Sellers should quickly become familiar with these tools to avoid falling behind in the AI-operations era.

4. Opportunities: More than 1.5 million merchants have used Jingmai AI tools, and daily active users have surpassed 500,000. The AI expert teams, full-chain AI diagnosis, and tool marketplace give sellers a low-cost path to professional operations capabilities. At the same time, JD.com's third-party good-tool recruitment program brings in more quality tools, reducing search and trial-and-error costs.

5. Cooperation: Sellers can join tri-party co-creation through the Jingmai AI Operations Center, working with the platform and service providers to codify standardized operating strategies and validate and iterate them in real stores.

The main takeaway for factories is that AI not only improves e-commerce operating efficiency, but can also feed back into product production and design, making factories more attuned to market demand.

1. Production and design needs: JD.com's AI Product Operations Center integrates various consumer data and offers merchants full-chain capabilities from demand mining to AI-launched managed operations. Factories can use such AI tools to analyze consumer questions and demand shifts, better judge which product functions and selling points are most popular, and use that insight to guide product design and production rather than working in a vacuum.

2. Business opportunities: AI shopping assistants are changing how consumers buy, with users moving from proactive search to direct questions. If a factory can clearly answer in its product pages what the product is, why it is good, and why it can be trusted, it can gain more exposure and orders in the AI-shopping arena. The article cites a merchant in the health-appliance category whose product-detail-page transaction value grew more than 20% month over month after using the AI Design Expert solution for 14 days, showing that AI can generate real gains in product presentation and conversion.

3. Digital transformation and e-commerce implications: JD.com is building an AI operations managed engine and moving toward full-managed store operations. Factories should build AI tool capabilities early, using Jingmai's AI expert teams, such as Hetu (product expert) and Sudangjia (product selection expert), to run one-click store diagnosis, batch modifications, and selection analysis. This reduces dependence on manual experience and gives factories low-cost access to professional operating capabilities. More than 1.5 million merchants have already used Jingmai AI tools, with AI daily active users surpassing 500,000, meaning the digitalization barrier is falling sharply.

4. Cooperation and co-creation: JD.com uses a platform + service provider + brand merchant tri-party co-creation model. Factories can also take part in building industry agents and professional skills, turning frontline production experience into AI-ready standards and gaining support better aligned with their own business.

For service providers, the article reveals an important industry trend: AI is moving from efficiency tools to operational intelligence, and the core opportunity for service providers is to transform from tool developers into operational co-creators.

1. Industry trend: The article says that AI first changed how e-commerce work is done and has now entered the stage of how businesses are run. Service providers need to understand this shift — merchants don't really need more tools; they need AI that can understand the business, diagnose problems, and continuously improve operating results. JD.com has already moved from giving tools to giving results and is gradually building an AI operations managed engine.

2. Customer pain points: Merchants commonly face too many tools, difficult onboarding, heavy operational workloads, and insufficient manpower. This gives service providers a clear direction: build smarter, more automated solutions around these pain points and help merchants move from single-point efficiency gains to full-chain intelligent operations.

3. Solutions: The Jingmai AI Operations Center integrates five modules and more than 60 AI tools, and opens a third-party tool marketplace. Service providers can use JD.com's platform entry points and AI product capabilities to turn frontline operational experience into SOPs, join AI expert-team co-creation, and develop industry agents and professional skills. The article cites Kunchi, a service provider that sorted out more than 150 operational processes, tested over 15 AI tools, and piloted with six leading industry brands — a clear example of deep ecosystem participation.

4. Cooperation and business opportunities: JD.com has launched a third-party good-tool recruitment program. More than 100 service providers have signed up, and over 20 have entered the official Jingmai merchant backend through the program, which gives them opportunities to reach merchants, exchange demand insights, and run pilots. Service providers should seize the window from tool placement to scenario co-creation and work with the platform to build industry-level solution tools, creating sustainable commercial opportunities.

For platform operators, the key takeaway is how JD.com uses AI to rebuild the merchant service system — from giving tools to giving results — and to strengthen platform competitiveness through ecosystem co-creation.

1. Latest platform initiatives: JD.com established the Jingmai AI Operations Center, which integrates five modules: Super Assistant, AI Experts, Full-Chain AI Diagnosis, a third-party tool marketplace, and merchant self-built tools. It brings together more than 60 AI tools that cover core processes such as store operations, opportunity-driven product selection, product content, marketing and promotion, order fulfillment, and customer service. JD.com also introduced an operations ontology technical architecture that connects natural language with e-commerce business logic, allowing AI to understand operating needs across multi-turn conversations.

2. Platform needs and challenges: Merchants have shifted from wanting tools to wanting results, so platforms must address pain points such as too many tools, difficult adoption, heavy operations, and insufficient manpower. JD.com's AI expert teams provide intelligent services for advertising, products, product selection, customer service, membership, and other scenarios, and let merchants use natural language to execute batch processing, automated inspection, intelligent store setup, and other complex actions.

3. Merchant recruitment and operations management: JD.com launched the third-party good-tool recruitment program to attract high-quality AI tools and service providers into the official Jingmai merchant backend. So far, more than 100 service providers have applied, and over 20 have joined through the program and are participating in AI expert-team co-creation. The platform's centralized integration lowers merchants' cost of searching for tools while giving service providers exposure and pilot opportunities, forming a healthy ecosystem.

4. Risk avoidance and control: JD.com relies on an end-cloud collaborative, controlled-execution mechanism that requires merchant authorization for all operations and full traceability of task processes. This reminds platforms that compliance, risk control, and trust mechanisms must be central when designing AI operating tools. At the same time, JD.com announced four major upgrades at its 2026 merchant conference — platform value proposition, first-party and POP synergy, increased support investment, and optimized business environment — to balance ecosystem relationships and avoid internal competition risks.

5. Operations and growth: More than 1.5 million merchants have used Jingmai AI tools, and AI daily active users have surpassed 500,000. The JD.com 11.11 shopping festival will drive the number of new merchants with sales above 1 million yuan to grow more than 60% year over year. Platform operators can learn from JD.com's path of making AI an engine for merchant growth.

For researchers, the value of this article is that it records the industry shift of e-commerce AI from efficiency tools to operational intelligence and provides a vivid case of business model transformation.

1. New industry trend: The article notes that after AI entered e-commerce, it first changed how things are done, and now it is moving into the stage of how to run a business. P&G has proposed a new AI operating paradigm — brands provide brand knowledge and strategy, while the platform provides data, tools, and AI capabilities. This paradigm shift means AI is moving from single-point task execution toward full-chain operational decision-making and is worth deeper study.

2. New questions: The article reveals the challenges of AI-based operations: merchants need AI to understand their business, know what the current problems are, decide what to do next, call on platform capabilities for execution, and continuously adjust according to results. This raises the core proposition that an AI that can perform tasks is only the starting point; an operational AI must continuously judge, execute, and optimize around business outcomes.

3. Business model: JD.com adopts a platform + service provider + brand merchant tri-party co-creation model. It uses the Jingmai AI Operations Center tool marketplace to host third-party AI capabilities and has launched the third-party good-tool recruitment program. Service provider Kunchi participated deeply in co-creation, sorting out more than 150 operational processes, testing more than 15 AI tools, and piloting with six leading industry brands. This ecosystem-based co-creation model is a typical case for studying platform-based AI commercialization.

4. Policy and regulatory implications: The article mentions JD.com's end-cloud collaborative, controlled-execution mechanism, which requires merchant authorization for all actions and full traceability of task processes. This highlights the importance of data security, operational transparency, and compliance risk control in AI operations, providing practical references for corporate governance and regulation.

5. Empirical data: The article provides quantitative evidence. For example, a health-appliance merchant using the AI Design Expert solution saw product-detail-page transaction value rise more than 20% month over month after 14 days; more than 1.5 million merchants have used Jingmai AI tools, and AI daily active users exceed 500,000; and JD.com's 11.11 campaign aims to grow the number of new merchants with sales above 1 million yuan by more than 60% year over year. These data points give researchers a basis for evaluating the value of AI operations.