Intelligent Transformation Path of Artificial Intelligence Algorithms and Engineering Management

As engineering projects expand in scale and increase in management complexity, traditional engineering management models are gradually revealing inefficiencies and lags in decision-making response speed, resource allocation coordination, and cross-process collaboration, making it difficult to meet the demands of intelligent transformation in engineering management. Therefore, this paper, from the perspective of engineering management decision-making and process reengineering, introduces artificial intelligence algorithms into the engineering management process, constructing a human-machine collaborative management path encompassing decision node identification, predictive support, and resource optimization. This improves the operational efficiency of engineering management through algorithm-assisted rather than replacement methods. Based on this, a comparative experiment is designed to verify the performance of traditional engineering management models and algorithm-supported management models in the same engineering scenario. Experimental results show that after introducing artificial intelligence algorithms, the average decision-making time in engineering management decreased from 42.6 min to 28.4 min, the decision response delay decreased from 11.3 min to 6.7 min, and the decision completion rate increased to 94.2%. Resource utilization increased from 76.8% to 85.3%, and the number of resource conflicts decreased from 14 to 6. The information consistency index increased from 0.71 to 0.83, and the management adjustment volatility significantly decreased. Meanwhile, the overall management performance was optimal when the human-machine collaboration weight was in the medium range, verifying the effectiveness of the intelligent transformation path of engineering management that combines algorithm-assisted and human decision-making collaboration. The research results provide an operable methodological framework and empirical reference for the intelligent transformation of engineering management.