How artificial intelligence promotes new quality productive forces of firms: A dynamic capability view

Tachia Chin, Zhisheng Li, Leping Huang and Xinyu Li

Technological Forecasting and Social Change, 2025, vol. 216, issue C

Abstract: Global economic growth has entered into the recovery phase of the economic cycle that is resilient yet slow, while the main culprit lies in the lower growth of green total factor productivity (TFP) caused by climate change intensification. It is imperative to formulate unconventional productivity models that can simultaneously solve ecological concerns and the crucial challenges posed by low innovation-driven productivity. This research aims to explore how and whether artificial intelligence (AI) as a critical dynamic capability to strengthen the development of firms' new quality productive forces (NQPFs). Based on the sample of Chinese manufacturing listed companies from 2011 to 2022, our findings show that AI promotes the development of firms' NQPFs; green innovation mediates the AI–NQPFs relationship, while economic policy uncertainty (EPU) moderates the above-mentioned mediating mechanism. Theoretically, our research extends Marx's view of productive forces to create a new construct of advanced productivity in China. Considering AI as a critical dynamic capability, we also provide insights into how productive forces are formed by human intelligence and AI. Practically, our findings help policymakers and practitioners reduce the impact of EPU caused partly by climate changes through AI usage and thereby predict the next trend of sustainable development.

Keywords: Artificial intelligence; New quality productive forces; Green innovation; Dynamic capability; Climate change (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0040162525001593
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:tefoso:v:216:y:2025:i:c:s0040162525001593

DOI: 10.1016/j.techfore.2025.124128

Access Statistics for this article

Technological Forecasting and Social Change is currently edited by Fred Phillips

More articles in Technological Forecasting and Social Change from Elsevier
Bibliographic data for series maintained by Catherine Liu ().