Ancillary information, such as apparent electrical conductivity (ECa), can improve the spatial and temporal estimation of soil properties. The purpose of this study was to determine if ECa could be used for the spatial characterization of soil organic C (SOC) within a long-term tillage experiment. Apparent electrical conductivity was measured using an electromagnetic induction sensor, the EM38DD, and its predictive potential for mapping SOC was evaluated. The ECa maps showed clear differences between the conventional tillage and direct drilling plots, with higher ECa and SOC in the direct drilling plots. A normalized ECa difference (ΔECa), calculated as the difference between the normalized vertical and horizontal dipole ECa values (ECaV and ECaH, respectively) successfully classified the SOC observations according to their corresponding management systems. Maps of ΔECa (FKM1) and ECaV and ECaH (FKM2) classified by fuzzy k-means accounted for 30% of the total SOC variability, whereas the individual plots and management strategy explained 44 and 41%, respectively. Simple kriging with local varying means using either FKM2 or plot-average SOC as secondary information reduced the RMSE by 8% and increased the efficiency index by about 70% compared with ordinary kriging. Despite the low point-to-point correlation between ECa and SOC, ECa was shown to be useful for the spatial estimation of SOC.