AIoT-infused sustainable commerce architecture integrating adaptive green intelligence and autonomous audit pipelines for sustainable operations.

The rapid growth of digital commerce has created an even bigger appetite for operational intelligence that is sustainable, transparent, and carbon-efficient. This work proposes AGIA2 (AI-driven Green Intelligence and Audit), an AIoT-infused sustainable commerce architecture that integrates adaptive green intelligence with autonomous audit pipelines to offer real-time environmental optimizations and Environmental, Social, and Governance (ESG)-compliant decisions. The method utilizes a mixed multi-modal dataset comprising e-commerce transaction logs, IoT supply chain sensor streams, carbon intensity time series, and audit/ESG compliance indicators. Such a dataset allows extensive modeling of the digital-physical-environmental interactions in modern commerce ecosystems. The proposed solution uses machine learning such as SVM, RF, and LR; deep learning like CNN and RNN/LSTM; and hybrid ensemble to derive sustainability scores, detect anomalies, quantify the operational emissions, and automate compliance. Adaptive Green Intelligence Module: This does carbon forecasting, energy optimization, and dynamic inference routing between edge-cloud layers. Autonomous Audit Pipeline will handle real-time audit checks, ESG rule validations, and explainable anomaly detection via SHAP/LIME. The proposed AGIA2 framework demonstrates superior performance compared to baseline models, including standalone Support Vector Machine (SVM), Random Forest (RF), Logistic Regression (LR), and Convolutional Neural Network (CNN) models, across key evaluation metrics such as accuracy, precision, recall, and F1-score in experiments with an accuracy of 96.1%, an F1-score of 96.0%, and a ROC-AUC of 0.98. It greatly decreases the false negatives of sustainability violations and increases audit confidence ratings. In the correlation and confusion matrix studies, there are significant dependencies between IoT activity, carbon intensity, and sustainability categories. The AGIA2 framework advances sustainable commerce towards a unified, real-time, AIoT-enabled method to run businesses sustainably, be carbon emission conscious, and audit themselves. Unlike fragmented AI-only or IoT-only approaches, AGIA2 embeds sustainability scoring and ESG-aligned auditability as core system functions rather than post hoc reporting layers.