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淘宝闪购骑士AI助手“小饿”日活超百万:从告诉“怎么办”到帮忙“直接办”

龚作仁 2026-09-11 11:38
龚作仁 2026/09/11 11:38

邦小白快读

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淘宝闪购骑士AI助手“小饿”是国内首个日活破百万的骑士端AI应用,既切实降低骑手工作负担,也能间接提升配送服务效率,相关核心信息值得大众了解。

1.基础情况:该AI助手2025年初推出,是国内首个基于大模型技术打造的骑士端智能体,依托自然语言处理、多模态交互、实时分析能力支持语音唤醒,今年夏天日活已超百万,主动服务累计超300亿次,覆盖骑手接取送达全流程的工作需求。

2.核心升级:近期完成功能迭代,从原本仅告知骑手操作方法,升级为可直接办理业务,覆盖绝大多数高频跑单场景。遇到商家出餐慢、联系不上顾客等问题,骑士语音呼叫就能直接完成报备、违规申诉,无需跳转页面;调整背单量、问题诊断等需求靠语音就能完成,还会主动提醒操作风险。

3.实际成效:语音提醒与操作、新人带练师傅、今日指南等五大功能累计使用均达亿级,超六成新骑士认可新人帮扶效果,还能有效降低安全事故,后续平台会继续扩展AI可直接办理的事项范围。

淘宝闪购推出的骑士AI助手“小饿”实现日活破百万、服务能力升级,反映了即时零售赛道履约端的技术升级趋势,对品牌布局闪购渠道、优化消费体验有参考意义。

1.渠道建设参考:当前即时配送平台正通过AI技术提升全链路履约效率,品牌在布局淘宝闪购等即时零售渠道时,可将平台的骑手AI服务能力纳入渠道选择的评估指标,这类能力可有效降低配送环节的异常损耗,提升配送时效稳定性。

2.消费体验优化方向:此前商家出餐慢、联系不上顾客等高频异常场景,需要骑手手动找入口报备、跳转操作,容易拉长配送时长影响消费者体验,现在AI可直接在对话内完成报备、申诉等操作,能大幅压缩异常处理时间,品牌可对应优化出餐时效告知、顾客预留信息提醒等配套流程,适配新的履约处理机制。

3.服务升级启示:平台同步搭配智能头盔、尾灯、手环“IoT三件套”与AI系统联动,为骑手安全和跑单效率护航,品牌在设计即时零售专属的产品、服务流程时,可结合这类履约端的技术配置,减少不必要的沟通成本。

淘宝闪购骑士AI助手“小饿”日活破百万且升级为直接办理业务,释放了平台加码即时零售履约效率的明确信号,闪购类卖家可从中把握经营优化方向与赛道机会。

1.经营风险降低提示:此前商家出餐慢、联系不上顾客等异常场景,需要骑手手动找规则、找入口报备,还要跳转页面操作,容易因报备不及时导致超时赔付、客诉等问题,现在AI可直接在对话内完成报备、违规申诉,大幅降低异常处理的时间成本,卖家只要按实际情况同步出餐进度,就能减少不必要的经营损失。

2.可借鉴的运营思路:平台的AI助手具备主动提醒、语音操作、新人带练等功能,针对高频需求解放从业者双手,卖家在自身店铺的客服响应、新员工培训、异常订单处理等环节,可借鉴这种“主动识别需求+简化操作流程”的思路,提升运营效率。

3.赛道机会提示:平台持续投入骑手端AI建设,还搭配智能头盔等IoT设备完善服务体系,后续还将扩展AI直接办理的事项范围,说明即时零售赛道的履约能力还将持续升级,卖家可提前布局适配平台的新履约规则,抓住即时消费的增长机会。

淘宝闪购骑士AI助手“小饿”的落地及配套IoT硬件的应用,为相关生产工厂指明了即时配送场景下的产品需求方向与数字化升级启示。

1.明确的产品设计需求:平台已推出智能头盔、尾灯、手环“IoT三件套”,与AI大脑联动为骑手跑单效率和出行安全护航,这类产品需要适配骑手户外跑单的场景,支持语音交互、实时数据同步、风险提醒等功能,相关硬件生产工厂可围绕骑手接取送达全流程的高频痛点,设计更适配AI系统的专用智能设备。

2.可挖掘的商业机会:当前“小饿”日活已超百万,主动服务累计超300亿次,五大核心功能累计使用均达亿级,覆盖全国大量骑手群体,后续平台还将扩展AI直接办理的事项范围,适配AI功能的骑手作业硬件、配套周边的市场需求会持续扩大,工厂可对接平台需求开发定制化产品,开辟新的业务板块。

3.自身数字化升级启示:工厂在自身的生产车间管理、自有物流团队管理环节,可借鉴这种“大模型AI+智能硬件”的服务模式,为一线作业人员配备可语音交互、直接处理高频问题的智能助手,降低一线人员的操作负担,提升整体运转效率。

淘宝闪购骑士AI助手“小饿”的规模化应用与升级,为即时配送相关服务商指明了行业技术落地趋势、一线从业者的核心痛点及可参考的解决方案方向。

1.行业发展趋势:即时配送赛道的技术落地已经从后端调度向前端一线作业场景延伸,从为从业者提供信息参考,升级为直接替代从业者完成高频、繁琐的流程性操作,AI智能体在蓝领一线作业场景的应用已经跑通规模化路径,日活破百万的成绩验证了这类产品的商业价值与用户接受度。

2.核心客户痛点:骑手群体的核心痛点集中在高频异常场景处理繁琐,比如商家出餐慢、联系不上顾客时需要手动查找规则、找操作入口报备,还要跳转页面完成操作,背单量调整等高频操作容易分散注意力,新骑士缺乏实时带教容易违规或引发安全事故,这些痛点此前缺乏高效的系统性解决方案。

3.可复用的解决方案:基于大模型、多模态交互、实时分析技术打造语音交互的AI智能体,将报备、申诉、参数调整等高频操作直接嵌入AI对话流程,搭配主动提醒功能,同时配套智能头盔等IoT设备,可覆盖从业者全流程作业需求,目前这类方案已经验证可有效提效、降低安全事故,超六成新骑士认可新人帮扶效果。

淘宝闪购落地骑士AI助手“小饿”并实现规模化应用的实践,为即时配送、本地生活类平台提供了骑手运营、履约提效的可复制经验,明确了平台服务升级的方向。

1.可参考的平台运营做法:2025年初推出国内首个基于大模型技术的骑士端智能体,依托自然语言处理、多模态交互等能力支持语音唤醒与智能响应,覆盖骑手接取送达全流程需求;近期完成升级,无需骑手跳转页面就能完成异常报备、违规申诉、背单量调整等高频操作,同时搭配智能头盔、尾灯、手环“IoT三件套”,构建AI+IoT的完整骑手服务体系。

2.运营优化的实际效果:目前“小饿”日活已超百万,主动服务累计超300亿次,语音提醒与操作、新人带练、异常作业辅助等五大功能累计使用均达亿级,平台调研显示超六成新骑士认为“带练师傅”功能帮助很大,有效降低了安全事故,既提升了骑手的服务体验,也能整体提升履约效率、减少配送纠纷。

3.后续运营方向提示:骑手端的效率与体验是即时配送平台的核心竞争力之一,平台可围绕骑手高频作业场景持续扩展AI可办理的事项范围,通过技术手段简化骑手操作、保障出行安全,既能提升骑手留存率,也能优化消费者的配送体验,构建差异化竞争优势。

淘宝闪购骑士AI助手“小饿”成为国内首个日活破百万的骑士端AI应用,是即时配送产业一线数字化的标志性事件,为相关领域研究提供了鲜活的实践样本。

1.产业新动向:大模型技术的应用场景已从C端消费、后端调度延伸至即时配送的一线作业环节,国内首个基于大模型打造的骑士端智能体已实现规模化落地,AI服务正从“提供信息参考”向“直接承接流程办理”升级,同时平台还通过搭配智能头盔、尾灯、手环“IoT三件套”,构建“AI大脑+智能硬件”的骑手服务体系,这是即时配送行业履约能力升级的新方向。

2.实践验证的核心价值:该AI助手2025年初推出,今年夏日活已突破百万,主动服务累计超300亿次,语音提醒与操作、新人带练、异常作业辅助等五大功能累计使用均达亿级,平台调研显示超六成新骑士认为新人带练功能帮助很大,可有效降低安全事故,验证了AI在一线蓝领岗位提效、保障安全、优化灵活就业群体工作体验方面的实际价值。

3.后续研究方向:目前平台还将持续扩展AI直接办理的事项范围,未来可围绕AI在灵活就业群体权益保障、作业风险防控、行业效率提升等方面的作用机制展开研究,也可针对这类一线AI应用的服务标准、责任界定等问题进行探索,为相关政策优化提供实践依据。

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Quick Summary

Taobao Flash Delivery’s rider-facing AI assistant "Xiao E" is China’s first rider-end AI application to surpass 1 million daily active users, as it tangibly reduces riders’ workload and indirectly improves delivery service efficiency. Key facts worth noting for the general public are as follows:

1. Basic profile: Launched in early 2025, Xiao E is China’s first large language model (LLM)-powered intelligent agent built for delivery riders. Supported by natural language processing, multimodal interaction, and real-time analysis capabilities, it supports voice wake-up. By summer 2025, its daily active users (DAU) had exceeded 1 million, with over 30 billion proactive service interactions delivered to date, covering riders’ full workflow from order pickup to final drop-off.

2. Core upgrades: The tool recently completed a functional iteration, evolving from only providing operational guidance to directly completing task processing for riders across most high-frequency delivery scenarios. For common issues such as slow merchant meal preparation or unreachable customers, riders can submit incident reports and file violation appeals directly via voice commands, without navigating across multiple app pages. Riders can also adjust order load limits, run operational issue diagnostics via voice, and receive proactive alerts for operational risks.

3. Real-world impact: Each of its five core functions—including voice-activated alerts and operations, onboarding mentorship for new riders, and daily task guidance—has recorded hundreds of millions of uses. Over 60% of new riders recognize the effectiveness of its onboarding support, and the tool has also effectively reduced safety incidents. The platform will continue to expand the scope of tasks that the AI can process directly in the future.

Taobao Flash Delivery’s rider AI assistant "Xiao E" has surpassed 1 million DAU and rolled out major service capability upgrades, reflecting the technology upgrading trend on the fulfillment side of the instant retail sector, and carrying reference value for brands building out flash delivery channel strategies and optimizing consumer experiences.

1. Channel development reference: Instant delivery platforms are currently leveraging AI technology to improve full-link fulfillment efficiency. When developing presence on instant retail channels such as Taobao Flash Delivery, brands can incorporate platforms’ rider-facing AI service capabilities into channel selection evaluation metrics, as such capabilities can effectively reduce abnormal losses in the delivery process and improve delivery timeliness stability.

2. Consumer experience optimization direction: Previously, high-frequency abnormal scenarios such as slow merchant meal preparation or unreachable customers required riders to manually find reporting entrances and navigate across pages to submit records, which often extended delivery times and hurt consumer experience. Now, the AI can complete reporting, appeal filing and other operations directly within conversation interfaces, drastically cutting exception handling time. Brands can accordingly adjust supporting processes such as meal preparation timeline notifications and customer contact information reminders to adapt to the new fulfillment processing mechanism.

3. Service upgrade insights: The platform has also rolled out a trio of IoT devices—smart helmets, tail lights, and wristbands—that connect with the AI system to support rider safety and delivery efficiency. When designing products and service workflows exclusive to instant retail, brands can align with such fulfillment-side technology configurations to reduce unnecessary communication costs.

Taobao Flash Delivery’s rider AI assistant "Xiao E" has exceeded 1 million DAU and upgraded to support direct task processing, sending a clear signal that the platform is doubling down on instant retail fulfillment efficiency. Flash delivery sellers can identify operational optimization directions and sector opportunities from this development.

1. Operational risk reduction guidance: Previously, in abnormal scenarios such as slow merchant meal preparation or unreachable customers, riders had to manually look up rules, find reporting entrances, and navigate across pages to submit records, which easily led to overtime compensation, customer complaints and other losses due to delayed reporting. Now the AI can complete incident reporting and violation appeals directly within conversation interfaces, drastically cutting exception handling time costs. As long as sellers accurately sync meal preparation progress in real time, they can reduce unnecessary operational losses.

2. Actionable operational insights: The platform’s AI assistant is equipped with proactive alerts, voice operation, and new rider mentorship functions that free frontline practitioners’ hands for high-frequency tasks. Sellers can reference this "proactive need identification + simplified operation process" logic across their own store customer service response, new employee training, and abnormal order handling processes to improve operational efficiency.

3. Sector opportunity signals: The platform continues to invest in rider-end AI development, and has paired the system with smart helmets and other IoT devices to improve its service system, with plans to further expand the scope of AI-processable tasks going forward. This indicates that fulfillment capabilities in the instant retail sector will continue to upgrade, and sellers can adapt to the platform’s new fulfillment rules in advance to capture growth opportunities in instant consumption.

The launch of Taobao Flash Delivery’s rider AI assistant "Xiao E" and the application of its supporting IoT hardware point to clear product demand directions and digital upgrade takeaways for relevant manufacturers in the instant delivery scenario.

1. Clear product design requirements: The platform has launched a trio of IoT devices—smart helmets, tail lights, and wristbands—that connect with the central AI system to support rider delivery efficiency and road safety. These products need to be adapted to riders’ outdoor working scenarios, supporting functions such as voice interaction, real-time data synchronization, and risk alerts. Relevant hardware manufacturers can design specialized smart devices better aligned with the AI system by targeting high-frequency pain points across riders’ full pickup-to-drop-off workflow.

2. Tappable commercial opportunities: Xiao E currently has over 1 million DAU, has delivered more than 30 billion proactive service interactions, and each of its five core functions has recorded hundreds of millions of uses, covering a large national base of riders. The platform will further expand the scope of AI-processable tasks going forward, driving sustained growth in market demand for AI-compatible rider work hardware and supporting accessories. Manufacturers can partner with the platform to develop customized products and open up new business segments.

3. Internal digital upgrade insights: For their own production workshop management and in-house logistics team management, factories can reference this "LLM AI + smart hardware" service model, equipping frontline workers with voice-interactive smart assistants that can directly handle high-frequency issues, reducing frontline staff’s operational burden and improving overall operational efficiency.

The large-scale application and upgrade of Taobao Flash Delivery’s rider AI assistant "Xiao E" clarifies industry technology deployment trends, core pain points of frontline practitioners, and replicable solution directions for instant delivery-related service providers.

1. Industry development trends: Technology deployment in the instant delivery sector has extended from back-end dispatching to frontline work scenarios, evolving from providing information reference for practitioners to directly replacing them in completing high-frequency, tedious procedural tasks. The large-scale adoption path for AI agents in frontline blue-collar work scenarios has been validated: the milestone of 1 million DAU proves the commercial value and user acceptance of such products.

2. Core client pain points: Riders’ core pain points center on cumbersome handling of high-frequency abnormal scenarios: for instance, when faced with slow merchant meal preparation or unreachable customers, riders need to manually look up rules, find operation entrances for reporting, and navigate across pages to complete operations. High-frequency actions such as adjusting order load limits can easily distract riders, while new riders lack real-time mentorship, putting them at higher risk of rule violations or safety incidents. These pain points previously lacked efficient, systematic solutions.

3. Replicable solutions: A voice-interactive AI agent built on LLM, multimodal interaction and real-time analysis technologies, which embeds high-frequency operations such as reporting, appeal filing and parameter adjustment directly into AI conversation flows, paired with proactive alert functions and supporting IoT devices such as smart helmets, can cover practitioners’ full workflow needs. This type of solution has been proven to effectively improve efficiency and reduce safety incidents, with over 60% of new riders recognizing the effectiveness of its onboarding support function.

Taobao Flash Delivery’s rollout and scaled application of rider AI assistant "Xiao E" provides replicable experience in rider operation and fulfillment efficiency improvement for instant delivery and local life platforms, and clarifies the direction of platform service upgrades.

1. Replicable platform operation practices: Launched in early 2025 as China’s first LLM-powered rider-end intelligent agent, Xiao E supports voice wake-up and smart response via natural language processing, multimodal interaction and other capabilities, covering riders’ full workflow from order pickup to drop-off. Its recent upgrade allows riders to complete high-frequency operations such as abnormal incident reporting, violation appeals and order load adjustment without navigating across app pages. The platform has also paired the system with a trio of IoT devices—smart helmets, tail lights and wristbands—to build a complete "AI + IoT" rider service system.

2. Verified operational improvement results: Xiao E currently has over 1 million DAU, has delivered over 30 billion proactive service interactions, and each of its five core functions—including voice-activated alerts and operations, new rider mentorship, and abnormal work assistance—has recorded hundreds of millions of uses. Platform surveys show that over 60% of new riders find the "mentorship" function highly helpful, and the system has effectively reduced safety incidents. It not only improves riders’ service experience, but also boosts overall fulfillment efficiency and reduces delivery disputes.

3. Future operational direction guidance: Rider-end efficiency and experience are core competitive advantages for instant delivery platforms. Platforms can continue to expand the scope of AI-processable tasks around riders’ high-frequency work scenarios, using technology to simplify rider operations and protect travel safety. This will both improve rider retention and optimize consumer delivery experience, building differentiated competitive advantages.

Taobao Flash Delivery’s rider AI assistant "Xiao E", which has become China’s first rider-end AI application to surpass 1 million DAU, is a landmark event in frontline digitalization of the instant delivery industry, providing a vivid practical sample for research in related fields.

1. New industry trends: LLM technology application scenarios have expanded from C-end consumption and back-end dispatching to frontline operation links in instant delivery. China’s first LLM-built rider-end intelligent agent has achieved scaled deployment, as AI services upgrade from "providing information reference" to "directly undertaking procedural task processing". Meanwhile, platforms are building an "AI brain + smart hardware" rider service system by pairing the technology with a trio of IoT devices—smart helmets, tail lights and wristbands—marking a new direction for fulfillment capability upgrades in the instant delivery industry.

2. Core value verified by practice: Launched in early 2025, the AI assistant surpassed 1 million DAU in summer 2025, with over 30 billion proactive service interactions delivered to date. Each of its five core functions—including voice-activated alerts and operations, new rider mentorship, and abnormal work assistance—has recorded hundreds of millions of uses. Platform surveys show that over 60% of new riders find the onboarding mentorship function highly helpful, and the tool effectively reduces safety incidents. This verifies the practical value of AI in improving efficiency, ensuring safety, and optimizing the work experience of flexible employment groups in frontline blue-collar positions.

3. Future research directions: The platform will continue to expand the scope of tasks directly processable by AI. Future research can explore AI’s mechanism of action in areas such as rights protection for flexible employment groups, work risk prevention and control, and industry efficiency improvement. Research can also explore issues such as service standards and responsibility demarcation for such frontline AI applications, to provide practical evidence for relevant policy optimization.

Disclaimer: The "Quick Summary" content is entirely generated by AI. Please exercise discretion when interpreting the information. For issues or corrections, please email run@ebrun.com .

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国内迎来首个日活百万的骑士AI应用。9月11日,记者获悉,今年夏天,淘宝闪购骑士AI助手“小饿”日活已超百万,主动服务累计已超300亿次,在骑士跑单各方面提供支持;同时,骑士助手已完成再次升级,从告诉“怎么办”到帮忙“直接办”,覆盖绝大多数高频作业场景。

AI“小饿”由淘宝闪购在2025年初推出,让城市骑士率先用上AI智能体。这是国内首个基于大模型技术打造的骑士端智能体,依托自然语言处理、多模态交互及实时分析能力,通过语音唤醒与智能响应,覆盖骑士“接取送达”全流程和日常工作全方位需求。

骑士的麻烦事,AI现在可以直接办了。据介绍,这次升级,让AI助手从以前告诉骑士“怎么办”,到现在帮忙“直接办”,成为更好用的跑单助手。

以商家出餐慢、联系不上顾客等为例,这是骑士最头疼的场景。现在,不用自己翻规则、找操作入口,骑士只需呼叫“小饿”,AI就可以判断能否报备、告知如何报备及权益等。“过去回答完,还要跳转其他页面操作,现在相关报备、违规申诉,可以直接在小饿内完成。”城市骑士蔡光轼说。

面对一些高频使用需求,包括调整背单量、诊断问题等,AI助手还能主动提醒、解放双手,骑士说说话就可完成。

据悉,AI助手在跑单提效、安全出行和新人帮扶等多方面大受欢迎。平台统计显示,语音提醒与操作、带练师傅、今日指南、异常作业辅助、申诉辅助等成为最受欢迎的五大功能,累计使用次数均为亿级。

(图说:淘宝闪购骑士AI助手让外卖骑士率先用上AI智能体,目前已从告诉“怎么办”升级为“直接办”。)

这些AI能力,让骑士跑单更省时安全,处理问题更轻松。以“带练师傅”为例,这是面向新骑士的专项服务,它就像一位24小时在身边的高手,能主动提供操作指引,主动提醒避免违规、错误操作,避开安全风险。平台调研显示,超六成新骑士认为帮助很大,并有效降低安全事故。

骑士AI助手是城市骑士AI智能服务体系的一部分。此前,淘宝闪购还在全国首发智能头盔、尾灯、手环"IoT三件套",与AI大脑一起,全程发力为骑士跑单和安全护航。

据悉,接下来,淘宝闪购将继续扩展AI直接办理的事项范围。其物流AI业务负责人表示,希望通过技术创新,让AI更好服务骑士,更好呵护城市烟火。

注:文/龚作仁,文章来源:Laborer,本文为作者独立观点,不代表亿邦动力立场。

文章来源:Laborer

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FAQ回顾

淘宝闪购骑士AI助手小饿是什么?

它是淘宝闪购2025年初推出的国内首个基于大模型技术打造的骑士端智能体,依托自然语言处理、多模态交互及实时分析能力,支持语音唤醒与智能响应,覆盖骑士“接取送达”全流程工作需求,目前日活跃用户已超百万。

淘宝闪购骑手遇到商家出餐慢、联系不上顾客等问题如何快速处理?

可直接语音呼叫骑士AI助手“小饿”,AI会自动判断是否符合报备条件,告知对应规则与权益,无需跳转其他页面,即可直接在小饿内完成异常报备、违规申诉等全流程操作,省去翻找规则、找操作入口的麻烦。

淘宝闪购骑士AI助手能给新骑手提供哪些帮扶?

它面向新骑士推出“带练师傅”专项服务,可24小时在线提供操作指引,主动提醒规避违规操作、避开安全风险。平台调研显示超六成新骑士认为该服务帮助很大,可有效降低跑单过程中的安全事故发生率。

淘宝闪购骑士AI助手最受骑手欢迎的功能有哪些?

据平台统计,语音提醒与操作、带练师傅、今日指南、异常作业辅助、申诉辅助是最受骑士欢迎的五大功能,各功能累计使用次数均达亿级,可有效帮助骑士提升跑单效率、保障出行安全、减轻工作负担。

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