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Automated agricultural machinery has advanced significantly in the previous ten years; however, the ability of such robots to operate safely will be critical to their commercialization. This study provides a holistic evaluation of the work carried out so far in the field of automated agricultural machines’ safety, as well as a framework for future research considerations. Previous automated agricultural machines’ safety-related studies are analyzed and grouped into three categories: (1) environmental perception, (2) risk assessment as well as risk mitigation, and (3) human factors as well as ergonomics. The key findings are as follows: (1) The usage of single perception, multiple perception sensors, developing datasets of agricultural environments, different algorithms, and external solutions to improve sensor performance were all explored as options to improve automated agricultural machines’ safety. (2) Current risk assessment methods cannot be efficient when dealing with new technology, such as automated agricultural machines, due to a lack of pre-existing knowledge. Full compliance with the guidelines provided by the current International Organization for Standardization (ISO 18497) cannot ensure automated agricultural machines’ safety. A regulatory framework and being able to test the functionalities of automated agricultural machines within a reliable software environment are efficient ways to mitigate risks. (3) Knowing foreseeable human activity is critical to ensure safe human–robot interaction.