Balancing sustainability and innovation: The role of artificial intelligence in shaping mining practices for sustainable mining development

Attaining sustainable development involves a mounting role in modern innovations especially in the mining industry. It is anticipated that the world's need for minerals will increase extensively. The research is of paramount significance as it scrutinizes how artificial intelligence can act as a central force in balancing sustainability and innovation within the mining industry for China over the period 1960 to 2022. In this regard, it paves the way for sustainable mining development and the resolution of pressing environmental and social issues. The finding of (ADF) Augmented Dickey-Fuller & Phillips Perron (PP) unit root tests advocate that variables follows order of integration 1 & (ARDL) bound test of Autoregressive Distributed Lag and Nonlinear Autoregressive Distributed Lag (NARDL) approve a long-term association between concerned variables. The ARDL and Fully Modified Ordinary Least Squares (FMOLS) results depict that the coefficient of artificial intelligence has a positive and substantial impact on mining sustainability in both the short-run (SR) and long-run (LR). Additionally, the outcomes of NARDL reveal that there lies an asymmetric LR relationship between artificial intelligence and mining sustainability. Additionally, the impact of economic growth, climate change, and political stability on mining sustainability has been examined. Based on the findings, it is proposed that incentives should be given to mining companies for investment and adoption of artificial intelligence-related activities and implement such policies that enhance transparency and accountability in the mining sector to attain sustainability, efficiency, and reduction in the social and environmental costs of various mining activities. •AI's Asymmetric Impact on Mining with shaping sustainability via AI in China's mineral industry 1960–2022.•AI Boosts Mining Sustainability with Positive, substantial effect on both short-run and long-run.•Equity, Efficiency, and AI: Unveiling an asymmetric link for greener mining practices.•AI Path to Sustainable Mining: Innovate for efficiency, minimize environmental and social costs.