Who is betting on Personal AI, and who is afraid of Personal AI?

Over the past month or so, China's Personal Agent sector has suddenly become crowded.

Alibaba is pushing Qianwen Go, Tencent is exploring a standalone personal Agent, ByteDance continues to extend toward system-level Agents on phones, StepFun has launched an agent phone, Ant has upgraded Lingguang, and Today AI has raised more than $200 million. Internet giants, model companies, and startups have all set their sights on personal AI assistants almost simultaneously.

But interestingly, just as companies are racing to launch their own Personal Agents, on October 14, the list of third-party apps that refuse automated operations, disclosed by Doubao Phone Assistant, included WeChat, Taobao, Meituan, and a large number of other high-frequency internet applications.

This precisely reveals a contradiction in China's Personal Agent industry: every company wants AI to become the user's new entry point, but not necessarily willing to hand over its existing entry point to someone else's AI.

Therefore, more worth pondering than whether Personal Agent will become the next hit application is this: is it actually creating a new AI market, or is it redistributing the users, traffic, and transactions that already exist in China's internet?

And this may be the true starting point for understanding the current competition in China's Personal AI.

From Chatbot to Personal AI, the collective pivot of the big platforms

Over the past few years, the consumer-facing competition among China's large-model vendors has gone through three rounds of goals.

First, competing on model capability: from 2023 to 2024, companies chased one another on answer quality, reasoning, search, and multimodality, and leaderboard scores were almost the entire topic of conversation.

Then, competing on user scale: from the price war in 2024 to the free-access shock brought by DeepSeek in early 2025, large-model apps opened up for free one after another, and with large-scale spending they expanded the pie.

Third, competing on task delivery: in 2025, Manus popularized the Agent concept, and AI began connecting tools and invoking services, trying to move from giving answers to delivering results; by 2026, Qianwen completed 120 million AI orders during the six days of Spring Festival—having AI complete transactions on people's behalf is no longer an engineering challenge.

This round of change is not a feature upgrade of Chatbot, but a change in the goal of competition: in the past, companies fought over a user's single question, a single search—once the answer was over, the value was realized; now they are fighting for the opportunity to continuously deliver tasks and needs for users. Whoever handles more tasks and for longer will understand users more deeply, and this relationship will be harder to replace.

What new value does Personal AI actually create?

It can be broken down into two kinds of demand.

One is incremental demand: things that no one could satisfy in the past because they were complex, trivial, and required long-term memory. Flight delay compensation is a typical example—to file a claim you had to queue for customer service and haggle over options, and many people simply gave up after doing the math. When the Agent itself checked the order, contacted customer service, refused the voucher and insisted on cash, and returned 70 yuan to the user's account, the abandoned demand was reactivated; this kind of demand did not fail to exist in the past, but the cost of handling it was higher than the benefit. The Agent pushed the cost close to zero, and service calls and transactions that would not have happened originally did happen.

Another is substitution of existing demand: booking tickets, shopping, comparing prices, making appointments—users used to do these themselves in apps, and now they hand them to an Agent. Only the path has changed; no new transactions are created.

The ratio between the two determines the direction of the industry. If the increment is large enough, this is a new market; if it is mainly migration of existing demand, then it is redistributing the traffic and user relationships of existing platforms. The answer is still unclear: Sensor Tower data shows that Meta's Muse surpassed 2.5 million downloads in 13 days after launch, with initial daily active users close to 3 times those of ChatGPT in the same period; but TickerTrends tracking shows that its average daily net new users subsequently fell from a September peak of 198,000 to 74,000, a drop of 62.4%. Curiosity has been proven; long-term high-frequency use has not.

The competitive logic of entry points has changed.

Once Personal AI takes hold, the competitive logic of entry points will change with it.

In the past, the core logic of platforms was to attract users into their own apps and complete search, selection, and transactions within the platform; Personal AI tries to split this step apart: users express their needs to AI, and AI decides which services to invoke and which platform to use.

The object of competition has shifted from "which app users stay in" to "who understands needs, organizes services, and decides the execution path." In other words, what is truly noteworthy about Personal AI is not that there is one more AI application, but that it may separate the demand entry point from the service delivery platform—and this separation opens up space for the next round of internet competition.

Different approaches to the same competition

Once the entry point may be separated, all parties must make their moves. Looking back at the actions of the past month or so in the context of each company's own foundations, there are five different paths: what each wants to gain and what it needs to protect determine its approach.

Alibaba's answer is Qwen Go: unveiled on October 13, embedded in the Qwen app rather than a standalone application. The first batch of demo scenarios—flight delay claims, Taobao price protection, and car maintenance inquiry and booking—involve long chains and many variables, and all of them fall within Alibaba's own ecosystem: claim payouts go into Alipay, and price protection is completed on Taobao.

At the Yunqi Conference in September, Qwen announced that it would build a Personal Agent based on the Agentic capabilities of Qwen 3.8 to serve 300 million users; previously it could already handle tasks in dozens of areas such as shopping, travel, and logistics, and Qwen Go extends its radius to long-running tasks that require repeated checking, communication, and comparison.

What is special about Alibaba is that it holds both a personal Agent and a transaction platform, covering the complete chain from demand to order. Qwen Go is more like an integrator of the old ecosystem than a new entry point—putting Taobao, Alipay, Amap, and Fliggy into one conversational entry point. The question is, as search, recommendation, and transactions are increasingly completed by AI, how will Taobao's bid ranking be priced?

Morgan Stanley predicts that China's monetizable consumer AI market will be about 300 billion yuan by 2030, with revenue still mainly from advertising and commissions—the pie may get bigger, but the people collecting the money may change. Keeping transactions within its own system is the key to Alibaba's answer. The rejection list includes 23 Alibaba-affiliated apps: its own Agent can touch Taobao, but others cannot.

Unlike Alibaba's bet on transactions, Tencent's trump card is connection. With WeChat in hand, Tencent has still rolled out multiple Personal Agent fronts outside WeChat.

At the end of September, the cloud-based personal assistant LightVela launched, connected through WeChat and online around the clock; in October, reports emerged that Tencent was developing a standalone app, "Yuanbao Assistant," giving it running space and permissions independent of the main Yuanbao app to handle long-cycle tasks and long-term memory; on PC, Marvis also upgraded its positioning in late September from "computer repair" to "AI butler," turning toward managing personal digital assets. A Citi report forecasts that at the end of the month Tencent will also update the products and strategies of Hunyuan Hy4, WorkBuddy, and Xiaowei.

Within WeChat, the moves are restrained. In June, WeChat published guidelines for mini-programs to connect to the AI ecosystem, and JD.com, Meituan, Ctrip, Didi, and others announced their participation; the native assistant "Xiaowei" began gray testing the same month, able to send messages and invoke mini-programs to place orders, with payments still confirmed by users, and in September it began internal testing of "Xiaowei AI Social." These moves point in the same direction: services go through mini-programs, payments go through WeChat Pay, and identity and relationships stay in WeChat.

WeCom is another entry point: on October 14, WorkBuddy entered the WeCom contacts as a bot, calling ten major capabilities such as messages, documents, meetings, and cloud drives within the scope authorized by the enterprise; QuestMobile data from September shows it is already the top office Agent by monthly active users.

The two lines run in parallel because WeChat is both Tencent's greatest advantage and its constraint: 1.4 billion monthly active users, relationship chains, and the service loop are all in WeChat, but this also means that every mistake an Agent makes within WeChat will directly transmit to Tencent's core business foundation.

So among the five companies, Tencent's posture is the most contradictory—it is closest to the core scenarios of Personal AI, and its cost of trial and error is also the highest, so it places more aggressive product forms outside WeChat, while WeChat itself only maintains small-scale testing within the gray-release scope.

Tencent's problem is that its entry point is too precious, while ByteDance's problem is that its entry point is not deep enough—its problem is not users; Doubao has over 100 million monthly active users and ranks among the top two domestic AI applications together with DeepSeek; what it lacks is permissions.

Doubao Mobile Assistant debuted last December with ZTE Nubia's engineering phone M153, and this September it released a consumer version; the NaviX Ultra carrying it went on sale, starting at 5,999 yuan, with nearly 400,000 reservations; internally it is also testing a personal assistant called "Xiaodou." The mobile assistant takes the GUI route: visual recognition to read the screen and simulated clicks, not relying on app vendors to open interfaces, but its operations bypass the apps' original interaction and distribution systems and easily run into risk controls—when the technical preview launched, there were incidents of WeChat accounts being forcibly logged out and Taobao logins being blocked.

On October 14, Doubao Mobile Assistant announced the results of the 30-day public notice of the SAEP protocol and also disclosed its rejection list: 155 apps, covering almost all high-frequency scenarios such as communications, social networking, e-commerce, travel, and payments, including 66 Tencent-affiliated apps and 23 Alibaba-affiliated apps; AI applications such as Qwen, Yuanbao, WorkBuddy, DeepSeek, and Kimi also reject one another.

ByteDance is betting on both apps and mobile operating systems because a standalone app cannot obtain execution permissions; only a system-level entry point can read and write the screen and schedule other applications. But this also makes it the party most dependent on others' openness: cross-app task handling is its core selling point, and this premise is precisely in the hands of the 155 apps that reject it.

The value of the path it bets on is built on the openness of other ecosystems, and the rejection list shows that others do not intend to open up.

ByteDance is moving from apps toward systems, while StepFun bundled models, systems, and terminals together from the start.

StepFun bundled models, systems, and terminals together from the start.

On July 13, it launched the AI terminal brand STEPX, the agent operating system Step AOS, and the personal agent Amoo; on October 13, its first agent phone, the STEPX Neo, was officially released, priced at 3,999 yuan.

In contrast to Doubao's GUI approach, StepFun takes the API partnership route: it calls the open service interfaces of partner vendors, initially connecting with Ctrip, Alipay, Didi, Meituan, and others—when a user raises a travel need, Amoo can book the itinerary, hail a ride, and make payment, stringing together a complete task chain. This route does not touch the core interests of app vendors and makes long-term partnerships easier to negotiate, but the pressure of ecosystem building falls entirely on StepFun: whether WeChat, Taobao, and Douyin are willing to open up directly determines how many tasks Amoo can complete.

Why would a model company build a phone? The large-model API business has been dragged into a price war, StepFun has no super app and lacks traffic like ByteDance's, so combining software and hardware is one of the few viable paths for it to gain a direct channel to users. It does not rely on hardware profits, does not do pre-installed ads, and has no hard shipment targets;

Chairman Yin Qi said: "Hardware is just a container; in the end, everyone is still using that Agent service." The cost is that the agent phone category has yet to be validated, and the premise for this bet to hold remains the openness of top apps.

Big companies either have an ecosystem to integrate or a user scale to distribute traffic to; Today AI has neither, and its only asset is an identity that does not depend on any platform. It was disclosed on October 21 that the company has completed a cumulative $200 million in financing, with investors including IDG Capital, Tencent, 5Y Capital, Ant Group, Sequoia China, Transsion Holdings, and others. Founder Qi Junyuan was previously vice president of product at Feishu and head of Doubao PC, and earlier founded Teambition.

Today AI has nothing except one identity: it does not depend on any platform. It was disclosed on October 21 that the company has completed a cumulative $200 million in financing, with investors including IDG Capital, Tencent, 5Y Capital, Ant Group, Sequoia China, Transsion Holdings, and others. Founder Qi Junyuan was previously vice president of product at Feishu and head of Doubao PC, and earlier founded Teambition.

The domestic version of Today AI launched on September 25, focusing on continuous observation and long-term memory: it proactively records itineraries, project summaries, and health conditions, and connects to applications such as WeCom, WeRead, Baidu Netdisk, Kingsoft Docs, and Tencent Meeting through Connector.

When big companies build a Personal Agent, they all have to answer "what if it cannibalizes our own apps"; Today does not need to protect any existing business model and can turn itself into an assistant that does not depend on a single platform. But its cross-platform capability relies on Connector, and Connectors are all held in the hands of the platforms.

More subtle is the capital structure: Tencent and Ant are both advancing their own Agents while both being its shareholders—this can be understood as a hedge, and it also means Today AI must keep its distance between the respective ecosystem interests of its two major shareholders.

Five paths, pointing to the same question

The five companies' paths are not mutually exclusive, nor are they necessarily final strategies, but together they show that competition in Personal AI has shifted from a comparison of model capabilities to a comprehensive competition of models, user relationships, service connections, operating permissions, and existing ecosystem resources.

Alibaba bets on transactions and fulfillment, Tencent guards high-frequency connections, ByteDance bets on distribution and terminal permissions, StepFun moves from models to operating systems and devices, and Today AI bets on cross-platform context. Existing advantages are the starting line, and also the constraints on the next stage of transformation.

Personal AI reshapes the internet, and the biggest variable may be China's super app ecosystem

All five approaches ultimately run into the same external condition: China's super app ecosystem. To see how special this wall is, we can first look at an overseas comparison sample.

The wall overseas, and the wall in China

On September 8, Meta released the personal agent Muse. It runs in an independent cloud virtual machine, and users assign tasks through a standalone app or WhatsApp; it can browse the web, fill out forms, place orders, and book itineraries on its own; at launch it connected with partners such as Spotify, OpenTable, Ticketmaster, and Plaid, and for services without partnerships it can still operate the browser like a human.

Overseas internet services are relatively fragmented, and interfaces and browsers leave a foundation for Personal AI to connect. Even so, conflicts still occur: on September 20, Amazon banned Muse's ability to place orders on behalf of users, citing unauthorized access, suspected storage of credentials, and failure to identify itself as AI—behind this is $68.6 billion in annual advertising revenue; when an Agent bypasses the homepage and search to go straight to ordering, ad slots lose their buyers.

China's situation is more closed. Overseas, it is point-like conflicts on fragmented services; in China, it is a super app system: WeChat and Weixin have over 1.4 billion monthly active users, and Douyin and Taobao are both 900-million-level entry points; services, transactions, payments, and user relationships are aggregated within a few platforms, with data isolated from one another. The rejection list of 155 apps is the most direct presentation of this barrier.

So in China, ecosystem integration capabilities beyond model capability may be the more critical element.

A contradictory competition.

Platforms face a dilemma. If third-party Agents help users compare prices and place orders, consumers no longer need to go through the e-commerce platform's full search, recommendation, and advertising path—the platform may gain new transactions, but it may also lose traffic distribution and commercial revenue; if it restricts third-party Agents, it may miss the opportunity to be invoked by the next-generation entry point.

More complicated still, the big companies' own Agents are also disrupting their own apps: Qwen Go bypasses Taobao's search and recommendations, and the future Yuanbao assistant will bypass service distribution within WeChat. So what Personal AI brings may not be "big companies versus startups" competition, but rather a self-transformation that the giants actively drive yet must handle cautiously.

The law has not delivered a ruling either. In August, the U.S. Court of Appeals for the Ninth Circuit vacated Amazon's preliminary injunction against Perplexity, on the grounds that it is the user themself who accesses the servers, and the AI is merely a tool—the conflict between Agents and platforms must ultimately be resolved at the commercial level. Some platforms are looking for a third path: WeChat does not choose open or closed; instead, it acts as the gateway itself, with services going through mini-programs and payments going through WeChat Pay. Meituan CEO Wang Xing said that, in addition to serving consumers and merchants, serving AI Agents is becoming increasingly important. If this path holds, future competition will not be "open AI versus closed Apps," but "who becomes the gateway that must be passed through."

The value chain may be cut apart again.

Future industry roles can be split into three layers: the user relationship layer—who continuously understands users and takes on personal needs and long-term goals; the intelligent orchestration layer—who decides which model, which tool, which service provider to invoke; the service fulfillment layer—who ultimately provides real services such as goods, content, payments, and mobility.

In the past, super apps integrated these three layers within a single platform, and this was precisely the foundation of their business model; Personal AI may cause them to gradually separate. The real question becomes: will user relationships, task allocation power, and transaction revenue belong to different companies in the future? That rejection list of 155 apps is the first round of answers from all parties.

Four questions that still have no answers.

First, cross-platform capability: can an Agent continuously and stably connect to a sufficiently broad range of services? SAEP and API partnerships are only the beginning.

Third, commercial sustainability: Morgan Stanley estimates that Meta's average revenue per user is about $70 per year, and the annual service cost corresponding to users consuming only 5% of the free quota reaches $124, exceeding the revenue contributed—whether costs can be covered, no one has yet proven.

Fourth, distribution of ecosystem interests: the Agent is responsible for selection, the platform is responsible for fulfillment—who gets traffic, data, revenue, and user relationships? This is the hardest one to resolve, because it is a question of interests, and interest questions are precisely the kind that China's super app ecosystem is best at creating and least good at conceding.

Back to the question at the beginning: who is betting on Personal AI, and who is afraid of Personal AI? The answer may be the same group of people. The bettors see the possibility of entry-point restructuring; the fearful worry about the depreciation of existing entry points—the two identities now overlap in almost all mainstream Chinese internet companies.

The real barrier in this competition may not lie in how much information about the user the AI remembers, but in whether it can reliably, stably, and at low cost translate a person's personalized needs into services completed across platforms. In China, this is both a technical issue and, even more, an ecosystem and commercial issue.