The conventional tourism route search methods have a narrow search range and a single optimal route selection, resulting in a significant amount of time and cost waste. In response to this situation, this study designed a regional tourism optimal route recommendation method based on ant colony algorithm, based on the background of the digital economy era. Firstly, the regional tourism route planning problem is abstracted as a traveling salesman problem, with the goal of minimizing the distance traveled by the traveling salesman, and a regional tourism optimal route recommendation model is constructed; Then, the ant colony algorithm is used to solve the model. Using ant colony algorithm to simulate the swarm intelligence behavior of ants foraging in nature, guiding ants to gradually approach the optimal solution through the accumulation and updating of pheromones. By continuously iterating and updating the concentration of pheromones, it ultimately converges to the globally optimal or approximately optimal tourist route. According to the simulation experiment, it can be concluded that this method is feasible.