The paper analyzes the use of Grover’s quantum algorithm to improve the efficiency of parameter optimization in economic models such as the Solow model and the Cobb-Douglas model. The effect of using a quantum algorithm on the accuracy and speed of finding stable stationary states is studied; these factors are crucial for studying long-term economic growth. It is revealed that quantum algorithms, in particular Grover’s algorithm, can speed up the process of determining optimal parameters. This significantly expands the capabilities of traditional analytical methods. The study of the interaction of quantum computing with classical models of economic growth allows for a deeper understanding of the mechanisms of economic processes and allows for modifying models for a more dynamic modern economy. The implementation of the developed quantum algorithms in the economy is proposed, which opens up new opportunities for forecasting and analyzing complex economic systems.