Economic Daily: AI slowdown not a bad thing, shift from wild growth to sustainability

Slowing down is not stagnation, and tightening is not a brake. Building a safety boundary and governance framework that matches technological capability is not the antithesis of industrial development—its true purpose is to steer AI from unchecked growth toward sustainable progress.

Two Landmark Events Shake Global AI Markets

Two major developments have recently emerged in the global artificial intelligence sector:

• Overseas leaders pause expansion: OpenAI and other leading AI companies have collectively proposed slowing the iteration pace of cutting-edge large models and temporarily shelving some expansion plans.
• China tightens IPO standards: Chinese regulators have tightened review standards for embodied intelligence companies seeking IPOs, introducing clearer and more standardized requirements for industry financing access.

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

Clarifying a Key Misconception

First, a critical misunderstanding must be corrected: slowing down is not stagnation, and tightening is not a brake.

While technological development and safety regulation have never been mutually exclusive, when AI capabilities begin to approach social safety red lines, it becomes necessary to address governance gaps in a timely manner. Establishing a safety boundary and governance framework that aligns with technological capacity is not opposed to industrial growth—it is essential for transitioning AI from chaotic expansion to sustainable development.

A Brief History of AI's Accelerating Trajectory

Looking back at the evolution 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. Scenarios once confined to science fiction are now being deployed in real-world test environments.

The Dual-Edged Sword of Rapid Innovation

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 immense opportunities, potential safety risks are also accumulating at an accelerated pace.

Recent overseas incidents—including 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 Industry Evolution

From this perspective, the proactive deceleration by leading companies and the tightening of capital market access by regulators represent an inevitable choice as the industry reaches a certain stage of maturity.

For some time, the global AI industry has poured resources into competing on iteration speed, racing to seize first-mover advantage. While this approach is common in emerging industries and can accelerate early-stage growth, unchecked sprinting inevitably breeds risks:

• Frontier model capabilities may have already exceeded the scope of technical control
• Overheated AI-themed capital markets, combined with immature business models, risk creating 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 makes building a fair and reasonable AI governance system increasingly important.

The faster AI technology advances, the more critical it becomes to:

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

Shifting Focus from Scale to Substance

When the industry stops competing solely over who has larger model parameters or faster iteration cycles, companies can redirect limited resources toward service innovation and scenario-based applications. This shift helps avoid:

• Risks from AI concept speculation for investors
• Industry "involution" and low-level redundant construction

These factors form the solid foundation for the long-term healthy development of the AI industry.

Balancing Innovation and Safety

Of course, risk should not lead to fear of development or innovation. From the perspective of industrial development patterns, 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 AI history. Its timely formation sends a clear signal to the international community:

Only by seeking balance between innovation and safety, and advancing with both prudence and ambition, can AI development stay on course. Only by guiding AI with human wisdom and international consensus can it truly become a powerful force for enhancing the well-being of all humanity and advancing human civilization.