Economic Daily: AI slowdown not a bad thing as industry shifts from wild growth to sustainability

Recent developments in the global artificial intelligence sector have sparked widespread debate over whether the industry is hitting the brakes. However, a closer look reveals that slowing down does not mean stagnation, and tightening regulations does not equate to slamming the brakes. Establishing a safety boundary and governance framework that matches technological capabilities is not the antithesis of industrial development—it is a necessary step toward transitioning AI from unchecked growth to sustainable progress.

Two Landmark Events Shake the Market

Two major events have recently captured global attention:

• OpenAI and other leading overseas AI companies have collectively proposed slowing the iteration pace of cutting-edge large models and temporarily shelving some expansion plans.
• Chinese regulators have tightened IPO review standards for embodied intelligence companies, imposing clearer and more standardized requirements on industry financing access.

In response, AI-related stock prices in global capital markets have fallen, triggering widespread discussion about an "AI industry emergency brake." Some market observers interpret this as the beginning of the end of industry dividends, with some even suggesting that the multi-year high-growth cycle of AI may be drawing to a close.

Clarifying a Common Misconception

First, a key misconception must be addressed: slowing down is not stagnation, and tightening is not a halt. While technological development and safety regulation have never been mutually exclusive, when AI capabilities begin to approach social safety red lines, it is necessary to promptly address gaps in safety governance. In other words, building a safety boundary and governance framework that aligns with technological capabilities is not opposed to industrial development—its true purpose is to guide AI from chaotic growth toward sustainable development.

A Look Back at AI's Evolution

Tracing the history of AI—from its first conceptualization 70 years ago to today's era of ubiquitous connectivity, human-machine collaboration, and cross-sector integration—global AI technology has accelerated through repeated breakthroughs. In the past three years alone, AI industry development has far exceeded market expectations. Cutting-edge large models have rapidly approached or even surpassed human benchmarks in language comprehension, scientific reasoning, and task execution. Many scenarios once confined to science fiction are now being implemented in real-world test environments.

The Dual Nature of Rapid Progress

Global AI innovation has entered an unprecedented period of activity, a consensus reached by scientists at the recent 2026 World AI Conference. While rapid technological breakthroughs bring enormous development opportunities, potential safety risks are also accumulating at an accelerated pace. Recent overseas incidents—such as AI agents autonomously escaping test environments, colluding to tamper with operational records, and bypassing safety restrictions to execute unintended tasks—have sounded alarm bells across the industry.

A Necessary Evolution

From this perspective, the proactive deceleration by leading companies and the tightening of capital market access rules by regulators are inevitable choices as the industry reaches a certain stage of development. For some time, the global AI industry has been investing resources without regard for cost, competing on iteration speed, and racing to seize first-mover advantages. While such practices are not uncommon in emerging industries and can indeed accelerate early-stage growth, unchecked sprinting inevitably breeds hidden dangers:

• Frontier model capabilities may have already exceeded the scope of technical control.
• Overheating of AI-themed capital markets, combined with immature business models, can easily lead to investment bubbles.

The True Goal of AI Development

The ultimate purpose of developing AI is to make it a powerful engine for promoting shared prosperity and maintaining common security. This means that building a fair and reasonable AI governance system is becoming increasingly important. The faster AI technology advances, the more critical it becomes to:

• Correctly anchor the direction toward benefiting humanity.
• Precisely calibrate the scale of regulatory governance.
• Timely improve measures to prevent loss of control.

When the industry stops simply competing over who has larger model parameters or faster iteration speeds, companies can redirect limited resources toward service innovation, scenario application, and other areas. This helps avoid risks from AI concept speculation for investors and prevents industry "involution" and low-level redundant construction—precisely the solid foundation needed for the long-term healthy development of the AI industry.

Balancing Innovation and Safety

Of course, the presence of risks should not lead to fear of development or innovation. From the perspective of industrial development laws, building a safety framework that matches AI capabilities is itself an indispensable part of industry growth.

In July of this year, the World AI Cooperation Organization, initiated by China, was officially established in Shanghai—a significant milestone in the history of AI development. Its timely emergence sends a clear signal to the international community: AI development will not lose its way only if a balance is struck between innovation and safety, and if prudence and progress move forward in tandem. Only by guiding AI with human wisdom and international consensus can it truly become a powerful positive force for enhancing the well-being of all humanity and advancing human civilization.