EcoScopeAI: An AI-Driven Carbon Accounting and Decision-Support Platform Enabling Sustainable Supply Chains and SME Decarbonisation, Alaeddine Boubaker
Alaeddine Boubaker
DBA Student, European School of Data Science and Technology
Germany
ORCID: 0009-0006-3952-9966
Paper Type: Research
DOI: 10.47556/J.WJSTSD.21.1-2-3.2026.12
Received: 13 October 2025 / Revised: 27 January 2026 / Accepted: 31 January 2026 / Published: 20 March 2026
Purpose: This research paper describes EcoScopeAI, an AI-powered carbon accounting prototype to assist small and medium-sized enterprises (SMEs) in meeting the requirements of two new EU regulations: the Corporate Sustainability Reporting Directive (CSRD) and the Carbon Border Adjustment Mechanism (CBAM). These regulations are designed to drive greater accuracy, automation and transparency in sustainability reporting in line with SDG 12 and SDG 13. The UK’s Department for Environment, Food and Rural Affairs (DEFRA) public dataset for emission factors is utilised to ensure transparency and reproducibility.
Design/methodology/approach: The study utilises a design science method integrating Natural Language Processing (NLP)-based auto-mapping, anomaly detection, clustering, and forecasting. We use open datasets such as DEFRA’s emission factors to promote transparency and reproducibility.
Findings: Originality/value of the paper: EcoScopeAI is a solution that uniquely combines AI-Automation, regulatory alignment and SME usability in a single architecture.
Research limitations/implications: Further validation on large datasets and across industries is mandatory.
Practical implications: EcoScopeAI supports affordable, AI-driven carbon accounting and decision optimisation for SMEs and exporters.
Keywords: CSRD; CBAM; DEFRA; SMEs; EcoScopeAI; NLP; Anomaly Detection; Clustering; Forecasting; Reinforcement Learning; SDG-12, SDG-13.
Citation: Boubaker, A. (2026): EcoScopeAI: An AI-Driven Carbon Accounting and Decision-Support Platform Enabling Sustainable Supply Chains and SME Decarbonisation. World Journal of Science, Technology and Sustainable Development (WJSTSD), Vol. 21, Nos. 1/2/3, pp. 199-214. WASD: London, United Kingdom.
