Artificial Intelligence in Agriculture: A Pathway to Improved Environmental Outcomes?

This study examines the effects of artificial intelligence (AI) investments in the agricultural sector on agricultural carbon dioxide (CO2) emissions. The study analyses nine countries that have made the most investments in AI technologies, using data from the period 2012–2023. The empirical analysis was conducted using a combination of the Panel‐Corrected Standard Errors method and the Method of Moments Quantile Regression technique. The findings suggest that AI investments in agriculture may have a positive and increasing effect on carbon emissions across quantiles. This effect was observed to be more pronounced at higher emission levels. Among the control variables, per capita income (GDP) generally exhibits a weak and negative relationship, while the rural population ratio has a significant positive effect on agricultural carbon emissions. In contrast, the trade openness variable plays a role in reducing emissions. The findings are significant for policymakers, environmental economists, and agricultural technology developers, as they highlight the need to carefully assess the environmental impacts of artificial intelligence investments and develop country‐specific sustainable strategies.