Enterprise Architecture in the Age of Generative AI: Adapting ERP Systems for Next-Generation Automation

Sanjiv Kumar Bhagat

International Journal of Scientific Research in Computer Science, Engineering and Information Technology, 2025, vol. 11, issue 2, 370-380

Abstract: Enterprise architecture is experiencing a profound transformation through the integration of generative artificial intelligence into Enterprise Resource Planning (ERP) systems, fundamentally reshaping how organizations approach automation, decision-making, and strategic planning. This article examines the architectural implications of incorporating AI capabilities into ERP frameworks, focusing on three key dimensions: predictive analytics for enhanced forecasting and risk management, intelligent process automation for operational efficiency, and strategic decision support through natural language processing. Drawing from industry implementations and architectural patterns, this article explores the challenges and opportunities in designing resilient AI-enabled ERP systems that balance innovation with enterprise constraints. The discussion encompasses critical considerations for enterprise architects, including data privacy, integration complexity, and governance frameworks, while providing actionable insights for organizations transitioning to next-generation ERP architectures. This article suggests that successful AI integration in ERP systems requires a holistic architectural approach that aligns technological capabilities with organizational objectives, supported by robust governance mechanisms and clear implementation strategies. This article contributes to the growing body of knowledge on enterprise architecture evolution in the context of emerging AI technologies, offering practical guidance for architects and decision-makers navigating this transformative landscape.

Keywords: Enterprise Architecture; ERP Systems; Age Of Generative; Generative AI Adapting; Systems For Next-Generation (search for similar items in EconPapers)
Date: 2025
Note: Article URL: https://ijsrcseit.com/home/article/view/CSEIT25112368
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Persistent link: https://EconPapers.repec.org/RePEc:jbh:ijsrcs:v11:y2025:i2:id:1104

DOI: 10.32628/CSEIT25112368

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