There is evidence to suggest that airborne droplets play an important role in the transmission of respiratory diseases. The highest risk of exposure to these pathogens is in indoor environments, where airflow control has been recognized as one of the most effective engineering means to combat its spread. However, this can contribute to a significant increase in energy costs, as conventional ventilation is often not designed to remove contaminants efficiently. In this study, Computational Fluid Dynamics simulations were used to analyze how a novel ventilation approach, called Personalized Displacement Ventilation (PerDiVent), can simultaneously reduce both pathogenic airborne transmission and reduce energy costs in an open office. In addition, thermal comfort and noise were investigated to assess the practicality of the concept. PerDiVent was found to reduce the risk of cross infection by a factor of 1.08–2.0 compared to mixing ventilation in the worst and best case scenarios analyzed, and lead to savings in mechanical power of at least 30%. Furthermore, there is great potential to further improve the system and to increase the stated numbers substantially with relatively simple alterations to the design. Tools that can be used to great advantage for such optimization are also proposed in this work. These include a simple integral model and analytical metrics to estimate the reduction in cross-infection risk and energy savings as a function of PerDiVent’s effectiveness in removing contaminants. Finally, the system has a modular and highly flexible arrangement, which makes it suitable for retrofitting purposes in various indoor environments and integration with current ventilation systems. The concept shows great promise for the future, where ventilation is required to create healthier and more sustainable environments.