Sneha Nej; Subhasree Bhattacharjee; Sudakshina Mandal; Rupa Saha; Jaya Kumari; Sreya Dey

A Review on Quantum Computing for Business Applications

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Author(s)

Sneha Nej ^1,* Subhasree Bhattacharjee ¹ Sudakshina Mandal ¹ Rupa Saha ¹ Jaya Kumari ¹ Sreya Dey ¹

1. Department of Computer Application, Narula Institute of Technology, Kolkata, India

* Corresponding author.

DOI: https://doi.org/10.5815/ijeme.2026.05.06

Received: 30 Apr. 2026 / Revised: 26 May 2026 / Accepted: 28 Jul. 2026 / Published: 8 Oct. 2026

Index Terms

NISQ, quantum computing, business intelligence, quantum approximate optimization algorithm, variational quantum eigen solver, quantum support vector machine

Abstract

Quantum Computing is gradually gaining importance as a transformative technology with the potential to revolutionize business applications by solving complicated problems beyond the capabilities of classical computers. Using basic principles such as superposition and entanglement, quantum systems can concurrently handle a wide range of combinations of possibilities. It offers several benefits in optimization, financial modeling, supply chain management, risk analysis, and machine learning. Despite the limitations of existing hardware in the NISQ era, rapid developments are enhancing scalability and reliability. This study analyses the practical implications, opportunities, and challenges of integrating quantum computing into business environments, spotlighting its capacity to drive innovation, competitive advantage, and long-term strategic growth throughout industries. By situating quantum computing within a transdisciplinary engineering and business ecosystem, this review demonstrates that quantum technologies are not merely enablers of computational speed but catalysts for systemic innovation.

Cite This Paper

Sneha Nej, Subhasree Bhattacharjee, Sudakshina Mandal, Rupa Saha, Jaya Kumari, Sreya Dey, "A Review on Quantum Computing for Business Applications", International Journal of Education and Management Engineering (IJEME), Vol.16, No.5, pp. 81-93, 2026. DOI:10.5815/ijeme.2026.05.06

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