Genomic selection (GS) can improve the efficiency of tea breeding compared to phenotypic selection (PS) by shortening the generation interval, increasing selection accuracy, and shortening the duration of the entire breeding program, especially at early stages. Tea (Camellia sinensis (L.) O. Kuntze) is mainly grown in low- to middle-income countries (LMIC) and is a global commodity. Breeding programs in these countries face the challenge of increasing genetic gain because the accuracy of selecting superior genotypes is low and resources are limited. Recurrent phenotypic selection has traditionally been the primary method for developing improved tea varieties and can take over 16 years. Therefore, the main objective of this study was to investigate the potential of implementing GS in tea breeding programs to speed up genetic progress despite the low labour costs in LMIC. We used stochastic simulations to compare three GS breeding programs with a commercial PS program over a 40-year breeding period. All GS breeding programs achieved higher genetic gains compared to PS. Seed-GSconst, in particular, proved to be the most cost-effective strategy for introducing GS into tea breeding programs. It introduces GS at the nursery stage, thereby increasing the predictive accuracy at the early stage of the breeding program. It also shortens the duration of the entire breeding program by three years and reduces the generation interval to two years. Our results indicate that GS is a promising strategy to improve genetic gain per unit time and cost in tea breeding programs.