The research explores opportunities for optimizing the development of the digital labor economy and human capital to support sustainable employment in the transportation sector within the Southern and Volga Federal Districts of the Russian Federation. Based on statistical data from 20 regions in 2022, the authors developed a regression model to analyze the effects that the growth of the digital labor economy has on employment in the transportation sector. This model was employed to evaluate how advancements in the digital labor economy influence sustainable employment in the transportation sector. It also aimed to differentiate between elements of the digital economy that promote sustainable employment and those that pose challenges to it. The authors identified trends from 2018 to 2022, forming the basis for alternative scenarios of developing the transportation segment of the digital labor economy in the Rostov Region up to 2026. The authors also outlined the contours of an optimization scenario for the transportation segment’s development. The key conclusion is that the prospect of optimizing the impact of the digital labor economy on sustainable employment in Rostov’s transportation sector by 2026 is tied to increased R&D activity in workplaces with varying degrees of automation and enhanced automation of ERP systems, with human capital at their core. The authors provide recommendations for optimizing the development of the transportation segment of the digital labor economy in the Rostov Region through 2026.