<p>Reducing carbon intensity is essential for sustainable industrial development in the United States (U.S.), yet it continues to fall short of its net-zero commitments. By addressing this challenge, our study conceptualizes several ecological modernization mechanisms, including Green and AI technology innovation index (GAIT), supply chain digitalization (SCD), private credit depth (PCD), supply chain efficiency (SCE), and GDP growth (GDPG) within an integrated framework to capture their long-run interactions with carbon intensity (CI) outcome of the country. Methodologically, our study employs the autoregressive distributed lag (ARDL) time series methodology, using the national level data from 1990 to 2023. Findings reveal that SCE shows the largest effect, with the most significant coefficient for reducing CI in the U.S., demonstrating the significance of efficiency in the industrial supply chain for successful decarbonization. In contrast, SCD increases CI rather than reducing it, due to emissions associated with high-tech digitalization. Nevertheless, GAIT exhibited a significant contribution to reducing CI in the long run, demonstrating the importance of Industry 4.0 innovations for sustainable industrialization. However, while PCD has no significant effect on CI’s long-term outcome, GDPG exhibits a significant potential for reducing CI in the long run. The robustness tests ‘FMOLS’ and ‘DOLS’ mostly confirm these findings. Moreover, Toda‒Yamamoto (TY) Granger causality test indicates unidirectional causal relationships from GAIT, SCD, PCD, SCE, and GDPG to CI, with the only reverse causality observed from CI to GAIT. All these findings are insightful for federal policymakers to emphasize effective ecological modernizers to reduce carbon intensity in the U.S., helping the country ensure sustainable industrialization and achieve carbon neutrality by 2050.</p>