Artificial Intelligence for Integrating Environmental Metrics into Management Accounting

Abstract

This research presents a novel methodological framework that integrates artificial
intelligence with management accounting to systematically incorporate environmental
metrics into corporate decision-making processes. Traditional management accounting systems have largely failed to internalize environmental externalities, creating a
significant 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 specialized
deep learning model trained on multi-source environmental data, and the Sustainability Inference Engine (SIE), a rule-based system that translates ecological impacts into
managerial accounting terms. The methodology was validated through a longitudinal case study involving three manufacturing firms over a 24-month period. Results
demonstrate that our AI-integrated system identified previously uncaptured environmental costs representing 12.8% to 18.3% of traditional operational costs, enabled more
accurate product pricing that reflected true ecological impact, and revealed strategic
opportunities for sustainable innovation that conventional accounting methods had
overlooked. 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 accounting
that moves beyond compliance-driven environmental reporting toward proactive ecological stewardship embedded within core business processes. The framework bridges
the persistent divide between economic and environmental performance measurement,
offering organizations a practical pathway to operationalize sustainability within their
management control systems