Artificial Intelligence for Integrating Environmental Metrics into Management Accounting (gjstudies, 2026)
This research presents a novel methodological framework that integrates artificialintelligence with management accounting to systematically incorporate environmentalmetrics into corporate decision-making processes. Traditional management accounting systems have largely failed to internalize environmental externalities, creating asignificant gap between financial performance and ecological impact. Our approach diverges from conventional environmental accounting by employing a hybrid AI architecture that combines symbolic reasoning systems with deep learning models to quantify,value, and integrate non-financial environmental data into existing accounting frameworks. We introduce the Environmental Cost Neural Network (ECNN), a specializeddeep learning model trained on multi-source environmental data, and the Sustainability Inference Engine (SIE), a rule-based system that translates ecological impacts intomanagerial accounting terms. The methodology was validated through a longitudinal case study involving three manufacturing firms over a 24-month period. Resultsdemonstrate that our AI-integrated system identified previously uncaptured environmental costs representing 12.8% to 18.3% of traditional operational costs, enabled moreaccurate product pricing that reflected true ecological impact, and revealed strategicopportunities for sustainable innovation that conventional accounting methods hadoverlooked. The system’s predictive capabilities allowed for forward-looking environmental budgeting with 89.7% accuracy in forecasting resource consumption variances.This research contributes a fundamentally new approach to management accountingthat moves beyond compliance-driven environmental reporting toward proactive ecological stewardship embedded within core business processes. The framework bridgesthe persistent divide between economic and environmental performance measurement,offering organizations a practical pathway to operationalize sustainability within theirmanagement control systems