A comprehensive evaluation index system is constructed, and the entropy weight TOPSIS method is used to measure the optimization level of the digital economy and tourism industry structure of 30 provinces in China from 2012 to 2021. Moreover, models such as quantile regression and panel threshold are used to explore the influence of the digital economy (DIG) on the optimization of the tourism industry structure (TIS) as well as its transmission mechanism. The study reveals that DIG significantly promotes TIS, which remains valid after endogeneity and robustness tests; the impact of DIG on TIS exhibited a “U-shape” effect that first decreases and then increases, and its highest significance is at the 90% quartile level. Threshold model tests revealed a nonlinear threshold effect with DIG and tourism total factor productivity (TTFP) as a single threshold and tourism technological progress index (TECH) as a double threshold, and the second threshold has the largest effect of 0.163. Mechanism analysis found that the mediating impact of the DIG on the TIS was mediated by increasing the TTFP, and the TECH accounted for the highest proportion of 12.15%. Regional analysis revealed that the role of DIG on the TIS is Central>East>West>Northeast, and the empowering effect is more significant in the high digital economy level area and the high tourism industry structure optimization area.