Quantum computing-Enhanced AI systems for advanced business intelligence applications

Taiwo, Itunu and Ogunbajo, Adeyinka and Abidola, Adefemi Quddus (2025) Quantum computing-Enhanced AI systems for advanced business intelligence applications. International Journal of Science and Research Archive, 14 (1). pp. 1839-1847. ISSN 2582 8185

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Abstract

The convergence of quantum computing and artificial intelligence represents a transformative technological paradigm with unprecedented potential for business intelligence applications. This comprehensive review critically examines the revolutionary capabilities of quantum computing-enhanced AI systems in addressing complex computational challenges across multiple business domains. Through systematic analysis of emerging research, implementation frameworks, and interdisciplinary case studies, we investigate how quantum computing's unique computational mechanisms can fundamentally reshape data analysis, strategic decision-making, and predictive modeling. Our comprehensive examination reveals that quantum AI systems demonstrate remarkable potential to reduce computational complexity by up to 90%, enhance predictive accuracy by 60-75%, and provide unprecedented insights across financial, logistical, and strategic business intelligence domains. The research synthesizes evidence from multiple technological domains, highlighting the transformative potential of quantum-enhanced AI in solving previously intractable computational problems. By exploring technological capabilities, implementation challenges, and future research directions, this review provides a critical framework for understanding the emerging intersection of quantum computing and artificial intelligence in advanced business intelligence applications.

Item Type: Article
Uncontrolled Keywords: Quantum Computing; Artificial Intelligence; Business Intelligence; Machine Learning; Optimization; Predictive Modeling
Subjects: Q Science > Q Science (General)
Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Depositing User: Editor IJSRA
Date Deposited: 09 Jul 2025 16:43
Last Modified: 09 Jul 2025 16:43
URI: https://eprint.scholarsrepository.com/id/eprint/234

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