As artificial intelligence (AI) continues to evolve, a plethora of large-scale models, products, and services are springing up, much like mushrooms after a rain. The ongoing enhancement of foundational large models, an ever-expanding array of AI tools, and the steady implementation of AI in various scenarios are propelling AI from the background to the forefront. Amidst the saturation of internet traffic, new growth primarily driven by AI is beginning to take shape. In response, some perceive AI as a tool and method for acquiring new traffic, while others view it as a catalyst for business transformation and sustainable long-term growth.

Whether AI serves as a tool for traffic acquisition and token sales or as a pathway for industrial transformation has become a pivotal question that every participant must confront. The answer to this question will directly influence how participants perceive and develop AI, as well as the role AI will play in the future development of industries.

The trajectory of the internet era has taught us that a development model solely focused on traffic without achieving industrial transformation and upgrading is unsustainable. Therefore, as AI matures and becomes the preferred choice for an increasing number of participants, we must provide a clear and resolute answer: AI should be the driving force behind industrial transformation, not merely a means to harvest traffic.

The Essence of AI Necessitates Its Deep Integration with Industries
As AI matures, particularly when it begins to integrate comprehensively and deeply with industries, we witness AI transforming industries from the inside out and from the bottom up. During this process, the elements, operational processes, and even the external manifestations of industries undergo profound changes. Ultimately, the transformation of industries by AI is a deep and comprehensive process.

This is the essence of AI. This essence dictates that only through deep integration with industries and by transforming them from within can AI truly propel industrial development into a new era. Only in this way can the functions and roles of AI be fully realized.

Moreover, the digital and data elements of AI are derived from industries. Therefore, industries serve as the foundation for AI. For AI to maximize its functions and roles, it must originate from industries, be applied to industries, and undergo a chemical reaction with industries. From this perspective, for AI to fully realize its potential, it must deeply integrate with industries and drive industrial transformation, thereby maximizing its value.

Furthermore, given the limited nature of traffic and the vast market size and long-term nature of industrial transformations, AI can play a sustainable role in the process of industrial transformation. Only by placing AI within the vast expanse of industries and continuously nourishing it with industry-specific data and insights can the development of AI be truly propelled to a new stage, and its value maximized.

The Subject of AI Necessitates Its Deep Integration with Industries
We all know that during the internet era, two major industrial categories emerged: the digital economy, represented by internet companies, and the real economy, represented by players in physical industries. It is worth noting that the digital economy and the real economy typically operate under different mechanisms and systems.

With the advent of the AI era, particularly with the acceleration of the integration of the digital and real economies triggered by AI, the subject of AI is no longer confined to a single industry like the internet but encompasses both the digital economy and the real economy. In this process, to maximize its functions and roles, AI must continuously strengthen its deep integration with industries and achieve the integration of the digital and real economies through such integration.

AI's industrial subject type, which spans both the digital and real economies, determines that it will not pursue traffic like the internet but will aim for industrial transformation and upgrading to find new development opportunities. In this process, the functions and roles of AI are not ultimately measured by the amount of traffic but by industrial transformation as an important indicator. Only by truly becoming the driving force behind industrial transformation, promoting industrial transformation and upgrading, and thereby maximizing its value and functions, can AI truly realize its potential.

The AI we see now is not only applied to the digital economy, represented by internet companies, but also to the real economy, represented by manufacturing, logistics, and healthcare. This is a direct manifestation of AI's subjectivity, which dictates that it should deeply integrate with industries to truly maximize its value, rather than merely pursuing traffic as its ultimate goal.

The Business Model of AI Necessitates Its Deep Integration with Industries
Another important reason why AI will not become a factory for selling tokens is determined by its underlying business model. We all know that during the internet era, the business model was primarily based on B2B and O2O models. Such a business model dictates that any participant, to achieve development, must rely on traffic. This is why we have witnessed the emergence of so many internet-era business models centered around scale and efficiency.

Unlike the internet, AI's business model is not supported by traffic but by industrial innovation and transformation. Through industrial innovation and transformation, AI achieves the deep integration of the digital and real economies on one hand, and the transformation of both the digital and real economies on the other. Through these two approaches, what is truly achieved is the transformation and upgrading of the supply side.

Through the transformation and upgrading of the supply side, the connection between upstream and downstream industries is no longer achieved through simple matching as in the internet era but through the precise reconnection of the supply and demand ends of industries. At this point, the connection between supply and demand is more driven by digital data, algorithms, and computing power to achieve efficient supply-demand matching. Therefore, AI's business model is based on the connection between supply and demand driven by the internal data, algorithms, and computing power of industries.

To achieve this, AI must deeply integrate with industries rather than merely being seen as a provider of tokens. Only when AI achieves deep integration with industries and finds ways and methods to reconnect supply and demand can its functions and roles be fully realized.

Conclusion
The nature, subject, and business model of AI dictate that it should deeply integrate with industries and become the driving force behind industrial transformation. For any participant who wants to make a difference in the AI era, only by abandoning the traffic-centric mindset of the internet era and truly placing AI within industries can they discover new development models and methods that differ from the past. Only in this way can AI truly become an internal driving force for the development and transformation of industries and main businesses, rather than becoming a token factory.