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Vol. 13 No. 02 (2026)
International Multidisciplinary Journal for Research & Development

Articles

TRANSFORMING LEGACY SYSTEMS WITH AI-ENHANCED QUALITY ASSURANCE AND CLOUD TECHNOLOGIES

Published 2026-02-16

  • Dr. Emil Novak

Dr. Emil Novak
University of Ljubljana, Slovenia

Abstract

The acceleration of digital transformation in contemporary enterprises has necessitated a paradigm shift in quality assurance (QA) practices, emphasizing the integration of automation and artificial intelligence (AI) into legacy system migration processes. This research critically investigates the interplay between cloud computing adoption, AI-driven QA methodologies, and enterprise digital transformation strategies, providing a comprehensive blueprint for migrating legacy QA systems to AI-augmented pipelines. Drawing upon empirical studies, theoretical frameworks, and industry reports, this study delineates the determinants influencing cloud migration decisions, the structural and organizational challenges associated with legacy system adaptation, and the technical nuances of implementing AI-assisted QA processes (Vaquero et al., 2008; Tiwari, 2025). The analysis incorporates historical perspectives on cloud computing evolution, market-oriented service delivery models, and microservice architectural patterns, elucidating their relevance to automated QA pipelines (Buyya et al., 2008; Taibi et al., 2016). The research underscores the importance of decision-support tools, risk assessment frameworks, and multi-cloud strategic planning, offering a detailed discussion of operational, managerial, and technological considerations. The findings demonstrate that AI-enhanced QA pipelines can significantly reduce testing cycles, improve defect detection accuracy, and optimize resource allocation while simultaneously mitigating the risks inherent in cloud adoption. This study contributes to both the academic and professional discourse on digital transformation by presenting an integrative model that harmonizes technological innovation with organizational strategy, thereby advancing the theoretical understanding and practical application of AI-driven QA in cloud migration contexts (Geelan, 2008; Khajeh-Hosseini et al., 2011).

Keywords

Cloud computing, Digital transformation, AI-augmented quality assurance

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References

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