Abstract: Digital technology constitutes an important driving force for promoting high-quality agricultural development. Based on resource orchestration theory, this study employs micro-level unbalanced panel data of agricultural-related enterprises listed on China’s A-share market over the period 2012-2024. By applying fixed effects models, double machine learning models, and mediation effect models, this paper empirically examines the impact of digital transformation on the total factor productivity of agricultural-related enterprises and explores the underlying mechanisms. The results indicate that digital transformation significantly improves the total factor productivity of agricultural-related enterprises, and this conclusion remains valid after a series of robustness and endogeneity tests. Mechanism analysis further shows that digital transformation enhances total factor productivity primarily by strengthening agricultural-related enterprises’ innovation capability and optimizing human capital. Heterogeneity analysis reveals that the productivity-enhancing effect of digital transformation is more pronounced for agricultural-related enterprises located in eastern regions, those with state ownership, and those engaged in planting and breeding activities, while the effects are relatively weaker for agricultural-related enterprises in the central and western regions, non-state-owned agricultural-related enterprises, and processing and manufacturing sectors. Based on these findings, governments should improve regional digital infrastructure, formulate differentiated digital transformation policies, and optimize the external environment for agricultural-related enterprises. Agricultural-related enterprises, in turn, should align digital transformation with their own development conditions, coordinate the allocation of capital, technology, and human resources, and choose appropriate digital transformation pathways.