This paper takes the ant colony optimization (ACO) clustering algorithm as the starting point, explores the innovative ways of enterprise strategic management based on the background of economic goals of carbon peak and neutralization, and dynamically adjusts the transition probability according to the average number of node branches to make it ‘explore’ and ‘utilize’. A balance can always be maintained between the two so that the algorithm can provide more technical support in realizing the innovation and practice of operation, profit, and management of enterprises while retaining a high searchability, avoiding stagnation, and ultimately promoting the sustainable development of the enterprise. The experimental results show that compared with the three conventional methods, the proposed algorithm has a robust global analysis ability, so it has a better application effect in operation, profit, and management of enterprise innovation and efficiency improvement. The application of ACO clustering can be seen.