The role of AI in automating enterprise payments: Enhancing speed, accuracy, and security

Sukumaran, Sutheesh (2025) The role of AI in automating enterprise payments: Enhancing speed, accuracy, and security. World Journal of Advanced Engineering Technology and Sciences, 15 (1). pp. 1912-1920. ISSN 2582-8266

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Abstract

This article examines the transformative impact of artificial intelligence on enterprise payment systems, highlighting how AI technologies are revolutionizing traditional financial operations through enhanced automation, security, and decision-making capabilities. The article explores multiple dimensions of AI application in payment ecosystems, including automated reconciliation processes that dramatically reduce manual workloads, sophisticated fraud detection systems that identify threats in real time, intelligent invoice processing that eliminates data entry burdens, and predictive analytics that enable proactive financial management. The article further investigates how these technologies are evolving toward autonomous financial operations where AI systems dynamically optimize payment flows, prioritize transactions based on comprehensive risk assessments, and ensure regulatory compliance without human intervention. While acknowledging significant implementation challenges related to legacy system integration, data quality requirements, regulatory considerations, and organizational change management, the article identifies pathways to successful adoption and examines emerging frontiers where AI convergence with blockchain, quantum computing, and conversational interfaces promises to deliver even greater transformations. This comprehensive article reveals how AI-powered payment automation is not merely improving operational efficiency but fundamentally redefining enterprise financial management as a strategic competitive advantage in the digital economy.

Item Type: Article
Official URL: https://doi.org/10.30574/wjaets.2025.15.1.0425
Uncontrolled Keywords: Payment Reconciliation Automation; AI Fraud Detection; Intelligent Invoice Processing; Predictive Cash Flow Analytics; Autonomous Financial Decision-Making
Depositing User: Editor Engineering Section
Date Deposited: 04 Aug 2025 16:15
Related URLs:
URI: https://eprint.scholarsrepository.com/id/eprint/3142