take the lead in building “National level AI application” It is becoming a central focus of competition among domestic high-tech giants.
ByteDance’s goal is to “Big Dubao”.
The Doubao app started as a chatbot. By integrating areas such as Douyin short video/e-commerce, Feishu, Qishui Music and Doubao Learning, it has gathered some of ByteDance’s most competitive products with the largest user base and significantly expanded its functional boundaries.
Tencent is developing “WeChat Agent”.
Tencent announced at the beginning of November last year that WeChat would launch an AI agent. Development of the WeChat agent has recently accelerated, and widespread external speculation suggests that it will be fully rolled out in the second half of this year.
Alibaba and Ant Group “Full suite of national level applications”.
Native AI app Qianwen serves as Alibaba’s core carrier in C-end AI usage scenarios. Meanwhile, existing applications such as Taobao, DingTalk, and Quark are also undergoing comprehensive AI transformation.
Ant Group also took important steps. In June, the AI version of Alipay launched ‘Abao’ to reimagine user experience and usage habits, using a direct conversational agent as a unified interaction gateway to traverse a large matrix of features and services. Recently considered an application with national potential in the market, Ant’s Afu is an amazing force that Ant is putting a lot of effort into nurturing.
On paper, All major companies are making significant gains in this race for “nation-level AI applications.”
But the problem they face is: A high DAU application is not equivalent to a “national level application.”
In the first half of the race for national-level AI applications, major companies have already sown the seeds. The focus of the competition then shifts to user mindset and ecosystem impact. It is at this stage that the gap really widens and the moat is built.
a
In addition to having a sufficiently large user base, a truly national-level application must also have the following characteristics:
on the other hand, It needs to be integrated into the user’s mindset and become the “default option” for a specific category of user needs.
All “national-level applications” in the mobile Internet era have this characteristic. People open WeChat for chatting, Taobao for shopping, Alipay for wealth management, and Douyin for short videos.
This preference, rooted in the logic underlying user decisions, gives these applications a moat that other applications cannot match or easily shake. Compared to fluctuations in the number of users, user mindset is much more stable and very important.
on the other hand, We need to form an ecosystem influence that can attract and collect upstream and downstream services.
Both WeChat and Alipay have built comprehensive mini-program ecosystems. With the participation of millions of merchants and institutions, the platform can infinitely expand its service capabilities without having to develop every service on its own.
Driven by the mini-program ecosystem, users scattered in niche long-tail scenarios are gradually drawn to the platform and form the habit of opening mini-programs first instead of third-party apps. This gives national-level applications the ability to grow sustainably and organically.
Of the three core metrics for national-level applications, user numbers are the most visible and easiest to achieve. By simply increasing your traffic investment and leveraging internal diversion, you can push your growth curve up in no time.
in contrast, User mindset and ecosystem impact will require consistent effort over time and will greatly test the patience and collective strength of leading companies.
User mindset is the “foundation” of national-level applications and determines users’ instinctive choices. Compared to the mobile Internet era, it is more difficult to cultivate user mindset in the AI era, and it is not easy to form a “default option”.
This is because AI applications have very distinct tool attributes. Users tend to “use what works better” and there are no migration costs between apps. At the same time, the lack of social attributes means that AI applications cannot lock down users through social connections.
In last year’s chatbot battle, AI apps owned by major companies took turns topping app store download rankings. But to date, no AI app can claim to be a chatbot. AI apps with a small user base can release new models or features and still attract a large number of users.
Building ecosystem influence for AI applications is far more difficult than for previous generations of applications.
B
Nevertheless, some AI applications are finding a viable path forward.
One important insight is that, first, “National level scenario” Rely on specialized capabilities to focus resources to achieve breakthroughs.
Afu, Ant Group’s AI health-focused application, is a notable case study worth noting.
The market is full of health applications, many backed by big technology companies. But overall, these applications are not large-scale. Even though concepts such as AI medical consultation exist, they have yet to gain widespread public attention.
Afu took a different approach. Targeting universal and essential needs such as health screenings and weight management, we strive to overcome the most core and common scenarios.
According to public data, there are about 300 million obese people in China, who are widely interested in how to lose weight and manage it, and are willing to invest time, energy and money in it.
To address this need, Afu launched the “100 Million Jin Scientific Weight Loss” campaign in early June. Users can not only check their own “contribution value” but also the total weight loss of all users nationwide, and can also receive red envelope rewards for continuous check-ins.
Ahu has also launched a campaign called “Get a body fat scale for 1 cent.” After purchasing a body fat scale for a few tens of yuan, users can link it to Afu and receive a full cash rebate, effectively paying only 1 cent, making the cost of participating in the national weight loss movement almost zero. In less than a week, more than 1 million body fat scales were claimed.
Meanwhile, Afu has also introduced a series of partners to achieve: Deep integration with them.
In early July, Ant Group acquired a stake in Bohi Health, making it the largest external shareholder with over 28% ownership. Founded in 2008, Bohee Health primarily provides services such as food tracking, weight management, and scientific weight loss plans, serving a total of 200 million users.
Through close collaboration between the two, Afu users can take photos of their food and let AI estimate its calorie content to assess its healthiness and get a more scientific and accurate weight management plan. Meanwhile, Bohee Health can leverage Afu as an AI health platform and extend its functionality to a broader group of C-end users.
This means that The value of AI applications to third parties is no longer just about driving traffic. By focusing on high-frequency scenarios, offering personalized plans to C-end users, and attracting more partners through close collaboration on B-end, Afu has gradually built a reputation that few competitors can match.
Another key insight is to leverage the benefits of existing ecosystems.
Alipay, another AI-powered national-level application from Ant Group, is also following this path. Launched in June, the fully updated AI version of Alipay (nicknamed “Abao”) has now completed intelligent adaptation to more than 100,000 services and 500 industry categories in its ecosystem, fully intelligently covering more than 8,000 scenarios ranging from daily life services to money management. Users can access a huge number of services through Abao.
Shortly thereafter, on July 7, Alipay capitalized on this momentum by officially launching the AI Open Platform, opening up AI integration capabilities to ecosystem partners including retailers, institutions, service providers, smart terminals, and large model platforms, making further progress towards intelligent business infrastructure.
Of course, this is also the direction that WeChat Agent is aiming for.
C
The strategies used by leading companies to build national-level applications in the AI era still have some inertia from the mobile internet era.
ByteDance’s “Big Doubao” and Tencent’s “WeChat Agent” differ in that one stands for “toolization of AI” and the other stands for “AI transformation of tools,” but they are both essentially the same. super app Currently being upgraded for the AI era.
Giant aims to make the most of its strengths and build a super entrance that covers all AI needs.
Currently, Doubao’s user size temporarily leads its competitors. WeChat Agent has received widespread attention even before its official release. Alibaba’s launch of a “full suite of national-level AI applications” is consistent with that philosophy. Full-stack implementation and group-wide joint operation.
Creating aligned and diverse business segments under a unified industry agenda and integrating them at the group and capital level to create synergies has always been Alibaba’s development path.
In the mobile Internet era, the central theme is “consumption,” which led to the construction of the Taobao e-commerce ecosystem, which has since been horizontally expanded into many fields such as payment, travel, local life services, mobility, and entertainment. In the AI era, the focus has shifted to vertical expansion, with the goal of becoming China’s only full-stack AI company.
Until now, external attention to Alibaba’s AI efforts has focused primarily on its infrastructure and model layers, including its homegrown chips, cloud computing capabilities, open source large-scale models, and MaaS platform. Currently, with the outstanding performance of AI apps such as Qianwen, Afu, and Abao, Alibaba’s national-level AI application matrix has gradually taken shape, something that other major companies have not yet achieved at this time.
However, Giant’s AI advances are not fully reflected in corporate valuations.
Under the influence of multiple factors, the capital market has focused much scrutiny on these Chinese Internet technology companies in recent years. However, the success of new AI applications like Afu proves that these large companies still possess strong AI innovation capabilities and have every opportunity to define the format and growth path of the next generation of national-level applications. They will not be left behind in the AI era. Rather, they are likely to be the first to secure a “ticket” to a new era.
This is basically a repeat of the story from the mobile internet era. As the era of mobile Internet access dawned, emerging startups flourished, while larger, somewhat slower-moving companies born in the PC Internet era faced widespread skepticism. But years from now, even after the competitive turmoil in the industry subsides and it enters a mature stage of development, the overall industry leader may still be that familiar name.
This article is from the WeChat public account “LetterHub” (ID: wjicaijing), written by Yan Fei, and published with permission from 36Kr.
