Modern Economics & Management Forum

Amid China’s strategic transition toward high-quality economic development, artificial intelligence (AI) has emerged as a pivotal enabler in catalyzing the formation of “new quality productive forces.” This study investigates the mechanisms through which AI enhances total factor productivity — specifically via reallocation of production factors, transformation of innovation paradigms, and advancement of green manufacturing. Anchored in a theoretical framework centered on the triad of “data–computing power–algorithm,” and illustrated through a case study in the chemical industry, the analysis delineates AI’s tangible contributions to accelerating R&D cycles, enabling autonomous manufacturing systems, and facilitating low-carbon industrial transitions. Empirical evidence from a large-scale industrial park based in Guangzhou demonstrates measurable improvements: a 0.9% increase in product yield and a 6.7% reduction in unit energy consumption within one year of intelligent transformation. The findings underscore the necessity of robust digital infrastructure and refined data governance as foundational supports for scaling AI-driven high-quality industrial development.