Intelligent Procurement Decision Support Framework using Artificial Intelligence for Enterprise Resource Planning Systems

Abstract

Procurement processes at enterprise level require bona fide validation and risk evaluation for financial compliance, operational transparency, and streamlined approval workflows. In this study, ASAP (Agentic System for Automated Procurement), a decision support system powered by artificial intelligence has been designed to improve procurement approval processes in enterprise ERP spaces. The suggested Architecture gets the information of purchase requisition from SAP S/4HANA using secure OData APIs. It has supplier, quantity, pricing, and delivery schedule details. A deterministic rule-based AI engine analyzes the compliance policy of the organization, supplier indicators of reliability, budget utilization thresholds, and procurement anomalies to assess procurement risks. The system produces interpretable risk scores and generates explainable advisory recommendations that aid the procurement manager and finance controller in an informed approval decision. The tests showed that decisions are taken consistently, audits can be traced well and delays in procurement approval are minimized. The suggested ASAP framework performs transparent and scalable intelligent procurement risk assessment while maintaining the transactional integrity of ERP and adherence to the financial governance policies of the enterprise.