The United States (U.S.) has one of the highest production-based ecological footprints (EFP) in the world. Consequently, reducing EFP is essential for ensuring ecological balance, protecting the environment, and reducing ecological degradation. However, the comparative analysis on the long-run associations of AI innovation (AIN), high-tech trade capability (HTTC), supply chain efficiency (SCE), information and communication technology investment growth (ICTIG), and GDP growth (GDPG) with EFP regarding the U.S. remains poorly understood. Using the autoregressive distributed lag (ARDL) method, this study shows a comparative analysis of the EFP’s determinants relying on the U.S. national level data from 1990 to 2023. Based on the ARDL findings, while AIN, SCE, and HTTC show statistically significant association with EFP in the long run, ICTIG and GDPG do not exhibit significant empirical association. Among three significant associations, AIN and SCE are associated with reductions in ecological footprint in the long run, indicating that the country has secured technology-driven ecological benefits and operational efficiency enhancement within the production dynamics by emphasizing AI innovation and efficient inventory management. In contrast, HTTC’s positive association represents significant ecological pressure with the high tech-industries technology advancement, driven by scale and rebound effects. All the results remained stable in FMOLS, DOLS, and CCR robustness tests. Besides, Granger causality indicates mixed predictive patterns of these relationships. The comparative analysis among these determinants' long-run associations with EFP significantly contributes to the single country level production-based ecological footprint literature and depicts several valuable empirical insights for policy actions by the federal government.