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AI-Driven Cloud-Based Scalable Architectures for Modern Enterprise Commerce and Digital Ecosystems

Dr Anisha Tandon
Department of Computer Science, Jagan Institute of Management Studies (JIMS), Rohini, New Delhi, India

Abstract

The rapid expansion of digital commerce has transformed enterprise information systems from relatively static transaction-processing platforms into continuously evolving digital ecosystems. Modern enterprises must simultaneously support high transaction volumes, personalized customer experiences, real-time decision-making, multiple digital channels, partner integrations, and rapidly changing business requirements. Cloud computing provides the elasticity and distributed infrastructure required for these demands, while artificial intelligence (AI) introduces capabilities for prediction, automation, personalization, optimization, and intelligent decision-making. However, integrating AI into cloud-based enterprise architectures creates new challenges involving scalability, data management, latency, security, interoperability, computational cost, model lifecycle management, and reliability. This essay examines AI-driven cloud-based scalable architectures for modern enterprise commerce and digital ecosystems, emphasizing how cloud-native principles, microservices, event-driven architectures, intelligent automation, distributed data platforms, and AI services can be integrated into a coherent enterprise architecture. The study proposes a research methodology based on quantitative experimental evaluation of representative commerce workloads under different architectural and AI configurations. Performance will be assessed using throughput, latency, scalability, resource utilization, cost efficiency, availability, prediction accuracy, and customer-experience indicators. Controlled experiments will compare conventional cloud architectures with AI-enhanced architectures across varying workload intensities. The proposed methodology seeks to identify architectural factors that improve scalability while controlling computational and operational costs, ultimately providing an evidence-based framework for designing resilient, intelligent, and adaptive enterprise commerce ecosystems

Keywords

Artificial intelligencecloud computingscalable architectureenterprise commercedigital ecosystemscloud-native systemsmicroservicesmachine learningintelligent automationevent-driven architecturepersonalizationscalabilityperformance engineeringenterprise systems

DOI

https://doi.org/10.15680/IRJIE.2023.0706007

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Publication Information

JournalInternational Research Journal of Innovative Engineering
Volume7
Number6
Pages13609-13620
Published2023-11-20
IssueVol. 7 No. 6 (2023): International Research Journal of Innovative Engineering (IRJIE)

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