In October of this year, OpenAI held its largest-ever developer conference, unveiling a new application development kit. This signifies that in the future, users will find it as easy to call third-party applications within ChatGPT as opening a website in a browser. OpenAI's goal is clear: to transform ChatGPT from a "use-and-leave" chatbot into a platform capable of handling more complex tasks, thereby keeping users engaged on ChatGPT for longer periods and establishing it as the traffic gateway for the AI era. Each era has its own traffic gateway; in the PC internet era, it was the browser, and in the mobile internet era, it was the application. Whoever controls the gateway defines the commercial rules of the era. As the battle for gateways intensifies, the B2B market cannot remain on the sidelines. Beyond OpenAI, Microsoft has integrated Copilot into its Windows and Office suite, while Google has deeply embedded Gemini into Workspace and Android. The giants share a unified objective: to make AI the default interface for people's lives and work, although the chosen paths and product forms have not yet converged. In China, DingTalk fired the first shot in this contest.

Just four months after the launch of AI DingTalk 1.0, DingTalk underwent another upgrade. In this minor version update, DingTalk completely shed the application architecture of the mobile internet era and was rebuilt as an AI-native work operating system, making it possible for AI to operate DingTalk and take over work tasks. The "AI DingTalk 1.1" new product launch and ecosystem conference signifies that work methods in the AI era are being reshaped, and the yet-to-be-defined paradigm for AI gateways has encountered new possibilities.

The version 1.1 update for DingTalk represents an attempt within Alibaba's broader product ecosystem to build an AI gateway amidst this wave of development. The fiercely contested battle for gateways has spread from the consumer (C-end) to the business (B-end) sector. Whether in the past or present, the strategies for C-end and B-end internet products are fundamentally different. C-end gateways aim to maximize user attention and create hit products; the essence of the B-end is to demonstrate ROI, reduce costs, increase efficiency, and provide optimal solutions to practical problems in daily business operations. In the generative AI era, the C-end approach is exemplified by "chatbots" like ChatGPT, Gemini, and Alibaba's Tongyi Qianwen, aiming to become personal super-assistants that solve problems, generate content, and plan tasks. The metrics for success lie in the model's generality,趣味性, and ability to form emotional connections with users. The B-end, represented by DingTalk and Microsoft 365 Copilot, aims to become collaborative platforms that enhance work efficiency, focusing on process reliability, understanding of vertical industries, and compatibility with existing enterprise systems. For applications like DingTalk with a substantial user base, the core challenge is the depth of their self-disruption.

Taking DingTalk's version 1.1 upgrade as an example, the "transformation" primarily revolves around three dimensions: First, the debut of AgentOS. DingTalk launched AgentOS as the world's first work intelligence OS built for AI, fundamentally altering DingTalk's original "application" positioning. It shifts from an office application requiring human operation to a work operating system that can command AI agents to operate other applications. Essentially, this upgrades AI from passively executing commands to being "proactive." Second, the introduction of the new DingTalk ONE, which is essentially a new interaction gateway for people and Agents. On this interface, work is pushed to people by AI in the form of an information stream. People can also use DingTalk AI Search to select any global large language model to work for them. Enterprises can use models like GPT-5.1, Gemini 3, and Nano Banana on DingTalk, provided it complies with laws and regulations. The role of DingTalk ONE is to change how work information is organized and interacted with, integrating information scattered across group chats, documents, and to-do lists into a single, AI-driven, prioritized information stream, shifting from "people seeking tasks" to "tasks finding people." Third, providing the AI hardware DingTalk Real, enabling every enterprise to have a secure environment for running AI agents. On one hand, through localized deployment, models, data, and applications are entirely contained within the enterprise intranet, fundamentally meeting the stringent compliance needs of industries like finance and government with high data security requirements. On the other hand, it offers an out-of-the-box, integrated software-hardware solution, allowing enterprises to have a dedicated, secure AI operating environment without complex development, thereby lowering the barrier to entry.

Summarizing DingTalk's upgrade strategy, the core lies in making AI not only understand tasks but also understand the company and the industry. Compared to the C-end, this requires longer-term accumulation and沉淀, but also implies that once conquered, the moat will "deepen with use." An enterprise is unlikely to use multiple work software applications with overlapping functions simultaneously. Whoever occupies this space first essentially locks in that enterprise's digital office scenario. As this exclusivity, combined with the accumulation of business data, process solidification, and system integration, further increases the cost of replacement and migration, it creates a powerful lock-in effect, building an insurmountable wall. This is why the B-end has become a crucial battleground in the current gateway war. The C-end can be instantly disrupted by new experiences, whereas the B-end is difficult to attack but easy to defend, with high customer stickiness and a focus on long-term value. Alibaba's advantage in the B-end lies in the fact that DingTalk itself is the "fortress gateway" that Alibaba already won during the mobile internet era, meaning Alibaba started this race more than a step ahead.

DingTalk stands as a benchmark Alibaba erected during the mobile internet era. "Opening DingTalk first thing at work" has long become the daily routine for tens of millions of Chinese enterprises, etched into the muscle memory of organizations like an immovable mountain for latecomers. On one hand, years of data accumulation mean DingTalk holds far more than just chat records; it contains a complete organizational chart, process architectures深入到具体业务, and the context of countless meetings and decisions. On the other hand, as DingTalk has become as embedded in daily operations as utilities, replacing it is not merely about swapping a tool but challenging the entire organization's磨合好的 communication rhythms, management habits, and collaborative默契. As generative AI disruptively changes the paradigm of human-machine interaction, the industry is watching to see how DingTalk will maintain its leading position. DingTalk's choice is to use AI to "remake itself from scratch."

The most significant change generative AI brings to workflows is the seamless integration of previously manual, fragmented processes. DingTalk's "remaking" involves "swinging three blades" at itself precisely around this point. The "first blade" cut towards interaction. The "AI DingTalk 1.1" version replaces complex menus and buttons with "DingTalk ONE." A simple command like, "Help me find the three products with the highest sales last quarter and make a PPT," allows the user to wait for the task to be completed. The "second blade" cut towards architecture. Through AgentOS, DingTalk upgrades itself into an operating system that can command AI to work—an AI dispatch hub capable of understanding complex instructions and automatically invoking functions like approvals, schedules, and documents to complete specific tasks. The "third blade" cut towards the ecosystem. Through the DEAP·Enterprise AI Platform, DingTalk provides a full-chain service from model management to application deployment, helping enterprises lower the barrier to creating agents. Essentially, it evolves from a tool-selling app store into a talent market for agents, further expanding the boundaries of the digital ecosystem.

What has caught the industry's attention is that these sweeping self-reconstructions have occurred within just a few months. Since the August release of AI DingTalk 1.0, DingTalk has maintained a rhythm of almost bi-weekly updates, leading to the thoroughly restructured version 1.1. Compared to Microsoft's journey of Office transformation starting in 2023, it can be said that DingTalk has covered in four months a distance that took its competitor two years. This depth and speed stem from the "full technology stack" Alibaba provides behind DingTalk: large language model "brainpower" from Tongyi Qianwen; computing power from the strong backing of Alibaba Cloud; and even self-developed chips at the底层 for support. It's like a race car driver who is not only highly skilled but also drives a car specially built by a top-tier team. In March of this year, Wu Zhao (known as "Wuzhao") returned to DingTalk, increasing investment in AI. Combined with the simultaneous DingTalk reforms, this "one-two punch" yielded immediate results, quickly producing several phenomenal AI products: AI Note Taker, developed through four months of joint training with the Alibaba Cloud team, saw its accuracy for Mandarin Chinese and dialect recognition rise to 90% (97% in specific scenarios). It has rapidly penetrated over 20 million enterprise organizations, becoming the most handy meeting note-taking companion for workers. The DingTalk AI Note Taker DingTalk A1 packaged this capability into a recorder-like device, bringing it from online to physical meeting rooms. It has already ranked first in sales on Tmall and Douyin for the C-end, and seen significant procurement for both new contracts and renewals in the B-end, becoming Alibaba's most breakout hardware hit in the AI era. DingTalk AI Spreadsheets gained attention as the "industry's first to support millions of hot rows," backed by a storage-computation integrated application architecture jointly developed by the Alibaba Cloud ADB-PG database team and DingTalk. Easier to use than low-code platforms, it allows functional department staff to solve business problems independently, potentially replacing some traditional low-code scenarios, and has become the most popular AI tool among grassroots employees.

Through this ground-up self-reinvention, DingTalk has once again secured an unassailable position in the B-end gateway battle. And with DingTalk as the pivot, Alibaba's gaze is directed towards a more distant goal—defining the value of AI for the entire industry's productivity.

At the Alibaba Group FY2025 Q3 earnings call, Wu Yongming, CEO of Alibaba Group and Chairman & CEO of Alibaba Cloud Intelligence Group, clarified DingTalk's strategic position—Alibaba's most important AI application asset targeting the enterprise end. In Wu Yongming's view, future enterprise internal systems will no longer be isolated functional modules but dynamic networks where multiple AI agents interconnect and invoke each other. Based on this understanding, DingTalk, as the super gateway hosting 700 million users and 26 million enterprise organizations, is being repositioned as a "natural language interactive enterprise intelligence hub." Behind this seemingly拗口 positioning lies Alibaba's precise understanding of the enterprise software revolution in the AI era, as well as a冷静 judgment of the ultimate vision of AI and its current stage. At the recent Yunqi Conference, Wu Yongming creatively proposed the concept of "Artificial Superintelligence" (ASI) and further pointed out that achieving Artificial General Intelligence (AGI) is now a certainty, but this is only the starting point; the ultimate goal is to develop ASI capable of self-iteration and全面超越 humans.

Simultaneously, Wu Yongming systematically outlined for the first time a three-stage evolution path towards ASI: Stage One is "Intelligence Emergence" (AI acquires generalized intelligence by learning vast amounts of human knowledge); Stage Two is "Autonomous Action" (AI masters tool use and programming capabilities to "assist humans"); Stage Three is "Self-Iteration" (AI connects with the physical world and achieves self-learning, ultimately realizing the goal of "surpassing humans"). Among these, AI connecting with the physical world is a cutting-edge direction currently garnering attention from both industry and academia. As early as the 1980s, computer scientists discovered a counterintuitive phenomenon: it's not difficult to teach a computer to play chess, but it's nearly impossible to give a computer the perception and行动能力 of a one-year-old child. This is the famous "Moravec's Paradox." This引出 the core dilemma that has plagued the AI industry for years: physical interaction. In the generative AI era, how to connect AI with the physical world remains an unavoidable challenge. Turing Award winner Yann LeCun has pointed out that existing large language models lack an understanding of physical reality. According to Wu Yongming's definition, the industry is currently in the second stage towards ASI. Whoever first masters the key to connecting AI with the physical world will be the first to open the door to the third stage,正如 Jensen Huang said, the next wave will be physical AI. For Alibaba, DingTalk is one of the "pass keys" to the third stage of "Self-Iteration."

The prerequisite for "Self-Iteration" is that AI can perceive the results of physical actions and obtain feedback. However, in work scenarios, a true connection between current AI and the real enterprise physical world does not yet exist. Therefore, Wu Zhao indicated that the most important aspect of DingTalk creating work methods for the AI era is to establish this connection, enabling physical world data to be understood and learned by AI, and allowing AI to influence the physical world through the tools it controls, making decisions and taking actions. The core of DingTalk's ongoing self-revolution lies in breaking down the walls of "virtual office," becoming a perceiver and actor in the physical world, attempting to actively connect and understand real enterprise sites. For example, in precision manufacturing companies, DingTalk AI no longer just answers questions but, by接入 sensor data, understands abnormal fluctuations in production lines, automatically generates contingency plans, and pushes them to relevant responsible persons, achieving a shift from "people seeking information" to "AI-driven decision-making." The essence is that DingTalk integrates underlying computing power, model capabilities, and upper-level business logic, providing enterprises with "plug-and-play" productivity for the AI era. Simultaneously, AI continuously obtains feedback data from real work scenarios, establishing a "closed-loop self-learning" system, becoming the nuclear reactor for enterprises to achieve qualitative leaps in productivity. In this process, DingTalk is redefining work methods in the AI era,酝酿 a "fission" in the productivity paradigm.

The ultimate value anchor of every technological revolution lies in how it changes human productivity. The Industrial Revolution replaced human physical labor with steam and machinery, reshaping manufacturing and transportation. The Information Revolution expanded human computing and communication capabilities with computers and networks, optimizing various industries, and further realized its full value through the industrial internet, enabling precise collaboration in global supply chains. Today, generative AI is broadening human cognitive and creative abilities. Its ultimate goal is to inject this cognitive intelligence into every link of the real economy's R&D, production, and operations, achieving an autonomous closed loop from perception, analysis, and decision-making to action. And this is also the core metric of the current gateway battle: whoever can establish a broad and reliable closed loop between AI and the physical world holds the key to defining the new round of industrial paradigms. From Tongyi Qianwen to DingTalk, Alibaba has率先亮出 its own answer.