AI Reshapes Growth Paradigms for China’s Digital and Real Economies

Artificial intelligence has evolved into a core driving force for global technological revolution and industrial transformation, restructuring traditional industrial boundaries and empowering the integrated development of digital and real economies across diverse sectors. Industry experts shared in-depth insights at the 2026 Capital Market Annual Conference’s Digital Economy Summit held on May 29, centering on AI-enabled industrial upgrading and the cultivation of new quality productive forces.

AI development has undergone remarkable structural changes in practical application. The technology previously served as an auxiliary tool for isolated industrial scenarios, constrained by insufficient industrial coordination and low value conversion efficiency. Continuous iterations of large models, computing power networks and intelligent algorithms have upgraded AI into a fundamental productive force. It now reshapes underlying growth logic for the digital economy, covering industrial structures, production factors, business models and capital operation mechanisms.

The real economy acts as the core carrier for AI value implementation. In manufacturing, industrial large models and intelligent scheduling systems facilitate flexible and intelligent production, effectively cutting operational costs and boosting overall productivity. In modern service industries including finance, logistics and commercial trade, AI optimizes resource allocation to support refined operation and upgraded service quality. In-depth integration between AI and traditional industries fosters innovative technologies, new business forms and modern operational models, consolidating industrial transformation and upgrading.

Capital markets provide robust momentum for AI industrial innovation. Continuous capital input supports technological research, scenario implementation and enterprise expansion. The A-share market has gathered high-quality enterprises focusing on computing power, large model development, AI application and digital infrastructure. The listing of digital economy enterprises also standardises industrial development and encourages sustained technological innovation across the sector.

The fast-expanding AI industry still faces systematic challenges in practical development. The sector grapples with insufficient high-end computing power supply, deficiencies in core algorithms, imperfect data security governance and inadequate industrial application standards. Shortages of interdisciplinary professional talents also restrict high-quality industrial progress. Partial market sectors exhibit excessive conceptual speculation and insufficient practical landing of AI technologies.

Targeted industrial optimisation measures are being advanced to address existing bottlenecks. Industrial participants prioritize independent technological breakthroughs to consolidate foundational supports of computing power, data and algorithms. All industrial stakeholders adhere to the principle of serving the real economy, regulating capital development and promoting in-depth AI integration with various industries. Improved supervision and security systems balance technological innovation and risk prevention, realizing coordinated progress between industrial development and standardized governance.

AI technological iteration and industrial integration will continue to drive industrial transformation and steady macroeconomic development. Continuous technological empowerment will unlock new growth potential for traditional industries and inject lasting digital vitality into high-quality economic development.