The article is devoted to the quantitative assessment of the contribution of green industrial automation to improving energy efficiency, decarbonization, and achieving sustainable development goals, taking into account the economic evaluation of external effects. The purpose of the study is to develop an integrated assessment methodology that combines direct financial results of digitalization and automation projects with the monetization of environmental and social externalities at the level of enterprises and industrial clusters. The empirical base consists of depersonalized data from 458 large enterprises in metallurgy, chemical industry, and mechanical engineering for 2018–2023 (over 150 thousand observations on energy consumption, emissions, and investments), supplemented by global statistical sources. The methodology includes panel data regression analysis with fixed effects to assess the impact of digital maturity indices and investments in “green” technologies on the energy intensity of revenue, the application of an extended cost–benefit analysis using the social cost of carbon and a dynamic discount rate, scenario modeling, and Monte Carlo simulations to assess the sensitivity of NPV and IRR to the volatility of energy carrier and carbon unit prices. It is shown that the implementation of comprehensive green automation systems reduces the specific energy intensity of revenue by 18–25% and operating energy costs by 15–20%, while ensuring a significant reduction in CO2-equivalent emissions and generating additional cash flow through participation in carbon markets and cross-border adjustment mechanisms. The calculations demonstrate that the NPV of the environmental component and the socially oriented profitability ratio (S-ROI>2) are comparable to the direct financial effect and in several scenarios exceed it, while the total integrated effect turns out to be higher than the simple sum of individual benefits due to the reduction of transaction costs and risks. It is concluded that the internalization of external effects radically changes the risk–return profile of green automation projects and provides a rationale for the formation of preferential financing regimes and regulatory support.