Globally, regions with robust industrial systems, abundant data resources, and diverse application scenarios are leveraging their market scale to serve as testing grounds for the intelligent economy. This has fostered a virtuous cycle of “demand-data-technology iteration.” Advancing the “AI+” initiative will further consolidate and expand these advantages, enhancing competitiveness in the international arena.
Data shows that artificial intelligence is developing rapidly across multiple countries and regions. Significant breakthroughs have been made in areas such as AI patents, humanoid robotics, and smart devices. A growing number of local governments are introducing policies to support the application of AI technologies. General AI literacy courses are also being gradually integrated into mainstream education systems to cultivate talent for the intelligent era. AI is accelerating its integration into all aspects of economies and societies worldwide.
From a policy perspective, many countries have established clear AI development strategies and timelines. These roadmaps typically include short-, medium-, and long-term goals, such as achieving deep integration of AI in key sectors within specific timeframes, increasing the adoption rate of smart devices and agents, and ultimately enabling the intelligent economy to become a major engine of economic growth before transitioning into a new phase of intelligent society trend.
The proposal of the “AI+” strategy marks a shift from perceiving AI as a purely technological concept or limited application to embracing its comprehensive integration with economies and societies. This trend focuses not only on technological breakthroughs but also on stimulating industrial dynamism, reshaping economic structures, and improving governance efficacy—representing a systematic approach to future development.
From an evolutionary perspective, the global economic paradigm has transitioned from the information economy to the digital economy, and now to the intelligent economy. The information economy built foundational networks enabling data flow; the digital economy turned data into productive factors, giving rise to platform models and online ecosystems; and the intelligent economy achieves a qualitative leap from “connection” to “empowerment” on this basis. Simply put, the information economy addressed “connectivity,” the digital economy unlocked “utility,” and the intelligent economy is building an ecosystem of “intelligence.” These three stages are not replacements but rather progressive, integrated, and symbiotic.
So, what does “AI+” actually mean? Economically, AI is reshaping the allocation of production factors, driving industries from digitalization to intelligentization, and creating a new economic paradigm characterized by human-machine collaboration and data-driven processes. For instance, in manufacturing, smart algorithms can dynamically allocate production resources and predict equipment failures, enabling more refined supply chain management. In agriculture, AI can optimize irrigation and fertilization strategies by integrating climate and soil data. AI is accelerating its empowerment across sectors, significantly boosting total factor productivity, shifting economic growth from scale expansion to quality enhancement, and fostering sustained endogenous growth momentum.
In the international competitive landscape, AI has become a new focus of strategic competition. Countries and regions with industrial foundations, data resources, and market advantages are able to form a “demand-data-technology iteration” cycle more quickly, thereby securing a more favorable position in global competition.
For the general public, the proliferation of AI will bring tangible and profound changes. It will become as ubiquitous as water and electricity—an essential service integrated into homes, transportation, health management, and other scenarios, delivering highly personalized and intelligent responses and services. Examples include dietary advice based on personal health conditions, traffic dispatch adapted to real-time road conditions, and more accurate disaster warnings and emergency responses, all of which will gradually become part of daily life.
However, the development of the intelligent economy also brings challenges. Issues such as data privacy, algorithmic fairness, and human-machine accountability require systematic governance. Key lies in balancing three relationships: the synergy between technology and ethics to ensure technological innovation and ethical governance advance together; the balance between innovation and security, encouraging innovation while strengthening safety safeguards; and the interaction between government and market, allowing governments to guide while fully stimulating the innovation vitality of market entities to form a healthy and orderly development structure.
