Even with advanced inverse intensity modulated radiation therapy (IMRT) technique, the optimization of treatment plans remains a time-consuming task and the outcome is highly influenced by the experience of the planner and time pressure. Automated treatment planning is a current hot topic and new frontier in radiotherapy, which is expected to minimize the above problems. The quality and efficacy of the IMRT plans generated by the Auto-Planning module of the Pinnacle(3) treatment planning system (TPS) were evaluated by comparing with traditional manual plans (MPs) for left breast cancer. Dose distributions of planning target volume (PTV) and organs at risk (OARs), treatment parameters including monitor units and number of control points, the planning time, and the quality assurance (QA) results were statistically compared for two types of treatment plans by Wilcoxon matched-pair signed-rank test followed by Bonferroni correction with a corrected significance threshold of 0.2%. Dose homogeneity of the PTV was better with automated plans (APs) (p < 0.001), but automatically generated plans showed inferior dose conformity (p < 0.001), when similar target coverage was obtained between the two planning methods. The low-dose distributions of left lung and heart were dramatically improved by Auto-Planning approach, which has the potential to reduce the risk of secondary cancer, and the V-5, V-10 and V-15 were respectively decreased by 15.9%, 14.7% and 8.8% for left lung and 43.1%, 39.2%, and 24.9% for heart, compared with the corresponding values for the human-driven plans (all p < 0.001). AP had a significantly lower mean dose for all OARs compared with MP (all p < 0.001). Meanwhile, the D-1 of contralateral breast was reduced by 1.86 Gy using Auto-Planning engine (p < 0.001). Additionally, significant difference was found for the average planning time (p < 0.001) which was reduced to just 10.10 min by using the Auto-Planning module. IMRT quality assurance was implemented by MartiXX detector, and both types of plans were practically acceptable on delivery and had no statistically significant differences. Moreover, the radiation oncologist preferred APs for all cases in terms of sparing of OARs. Overall, the evaluated automated planning algorithm is a good option for treating left breast cancer, which generates high quality treatment plans quickly and effectively. Auto-Planning method has wide clinical applicability since it is in favour of sharing knowledge and standardization of treatment plans.