Economic Daily: Saying Goodbye to Wild Growth, AI Slowing Down Is Not a Bad Thing

Recently, two landmark events have occurred in succession in the global artificial intelligence field: leading overseas AI companies such as OpenAI collectively proposed slowing the pace of iteration of frontier large models and temporarily shelving some expansion plans; meanwhile, China's regulatory authorities tightened IPO review standards for embodied intelligence companies, setting clearer and more standardized requirements for financing access in the industry. For a time, AI-concept stock prices in global capital markets fell in response, and discussions about an "AI industry sudden brake" have been rising one after another. Some market participants interpreted this as the beginning of the fading of industry dividends, and even believed that the AI high-growth cycle that has lasted for several years will come to an end here. First, a misconception must be clarified: slowing down does not equal stagnation, and tightening does not equal hitting the brakes. Although technological development and safety norms have never been in a mutually exclusive relationship, when the capability boundaries of AI technology have gradually expanded to the red line of social security, it is necessary to promptly fill the shortcomings of safety governance for the industry. In other words, building safety boundaries and governance frameworks that match technological capabilities is not the opposite of industrial development; its real purpose is to let AI move from barbaric growth to sustainable development. Looking back at the history of artificial intelligence development, from the first proposal of this concept 70 years ago to today's intelligent connection of all things, human-machine collaboration, and cross-boundary integration, global AI technology has accelerated its iteration through major breakthroughs again and again. Especially in the past three years, the development of the AI industry has far exceeded market expectations. The capabilities of frontier large models in multiple dimensions such as language understanding, scientific reasoning, and task execution have rapidly approached or even partially surpassed human benchmarks, and many scenarios that previously existed only in science fiction works have begun to be implemented in real test environments. At present, global AI technological innovation has entered an unprecedented period of activity, which was the consensus of scientists at the 2026 World Artificial Intelligence Conference not long ago. While rapid breakthroughs in AI technology bring huge development opportunities, potential safety risks are also accelerating their accumulation. Recent overseas incidents, such as AI agents autonomously escaping the test environment, collaboratively tampering with operation records, and bypassing safety restrictions to perform unexpected tasks, have already sounded the alarm for the entire industry. In this sense, the leading companies' voluntary slowdown and the regulatory authorities' tightening of capital market access rules are essentially inevitable choices after the industry has developed to a certain stage. For some time, the global AI industry has invested resources regardless of cost and competed over iteration speed, trying to seize the industry's development opportunities at the fastest speed. This practice is not uncommon in many industries and objectively did play a role in rapidly advancing the industry during its embryonic stage, but running forward without limits will inevitably bring many hidden dangers. For example, the capabilities of frontier models may already exceed the scope of technical control, while the overheated AI theme in the capital market can easily trigger investment bubbles when business models are not yet mature. The ultimate purpose of developing artificial intelligence is to make it an important source of power for promoting common prosperity and safeguarding common security, which means that building a fair and reasonable AI governance system is becoming increasingly important. The more rapidly AI technology develops, the more correctly we must anchor the direction of striving upward and toward good and benefiting humanity, the more precisely we must grasp the scale of regulatory governance, and the more promptly we must improve measures to prevent loss of control. When the industry no longer simply competes over whose model has larger parameters and faster iteration, it will instead help companies direct limited resources to areas such as service innovation and scenario applications, avoid the risks that AI concept speculation brings to investors, and the industry "involution" and low-level repetitive construction that may arise from it. And these are precisely the solid foundation that supports the long-term healthy development of the AI industry. Of course, we cannot refrain from development or even fear innovation just because there are risks. From the perspective of industrial development laws, building a safety framework that matches AI capabilities is itself an indispensable part of industrial development. In July this year, the World Artificial Intelligence Cooperation Organization, initiated under China's leadership, was officially established in Shanghai, which can be called an important milestone in the history of AI development. Its timely emergence sends a clear signal to the international community: only by seeking a balance between innovation and safety and moving forward in coordination with prudence and enterprise will AI development not lose its direction; only by adhering to leading development with human wisdom and international consensus can artificial intelligence truly become a powerful positive force that enhances the well-being of all humanity and promotes the progress of human civilization.