The insertion of information and communication technologies can cause mismatches between supply and demand of the workforce. In this sense, the objective of this study was to investigate the determinants of employability in the agricultural sector in times of industry 4.0. For this, a logistic regression model was used in order to estimate the probability of a given worker being employed, given a set of explanatory variables. This work innovated by inserting the automation probabilities associated with occupations estimated by Frey and Osborne (2013) and LIMA et al. (2019) as an explanatory variable for the employability of workers in the agricultural sector. The database used in this research was RAIS year 2019. The main results found indicate that schooling, time of employment and income positively impact the probability of the individual being employed, in all five Brazilian regions; while individuals who are associated with occupations that have a high probability of automation, have an expected probability of being employed lower than those associated with a low probability.