Introduction: Under the dual pressures of farmland protection and rural transformation, China’s farmland regulation faces two major challenges: conversion to non-agricultural uses and the expansion of non-grain cultivation. The traditional bureaucratic regulatory regime has exhibited structural failure in addressing these issues. Methods: Using County M as a case, this study examines how for-profit organizations optimize the structure and effectiveness of county-level farmland regulatory networks. Social network analysis (SNA) is employed to quantitatively assess changes before and after the introduction of for-profit organizations (designated as S-type nodes). Results: After the introduction of for-profit organizations, administrative centralization decreased from 27.62% to 24.51%, normative heterogeneity increased from 0.24 to 0.37, and network density and compactness rose to 0.5000 and 0.738, respectively. The average path length shortened to 1.573, fragmentation declined to 0.262, and the number of cohesive subgroups grew by 66.7%. Among these actors, S1 emerged as a structural hub embedded across multiple subsystems, enhancing regulatory responsiveness and reducing policy implementation bias. Discussion: This study moves beyond the Western nonprofit-oriented path dependence in collaborative governance research and, within China’s public land ownership context, reveals how for-profit organizations improve governance effectiveness through structural embeddedness. It translates multi-actor coordination into quantifiable network parameters, clarifies the interaction logic between for-profit organizations and bureaucratic institutions, and demonstrates its impact on network performance. The findings provide quantitative evidence and a replicable approach for shifting farmland regulation from institutional restructuring to structural reshaping.