Cost Savings Through Quantum AI-Driven Optimizations

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Authors: Pranali Dhawas, Pranali Faye, Pooja Pimpalshende, Kaveri Samir Deosarkar, Rajendra M. Rewatkar, Devendra Joshi
Cited by: 0
References: 8

Abstract

This chapter explores the transformative potential of Quantum Artificial Intelligence (QAI) in driving significant cost savings across various business operations. As organizations face increasing pressure to optimize resources and enhance operational efficiency, traditional computational methods often fall short in addressing complex, large-scale problems. Quantum AI, which synergizes the computational power of quantum computing with advanced machine learning techniques, presents a promising solution. This chapter delves into the theoretical underpinnings of QAI, showcases real-world applications in logistics, supply chain, finance, and manufacturing, and provides a comparative analysis of cost efficiencies achieved through QAI-driven optimizations. Case studies and empirical evidence highlight how QAI not only accelerates decision-making but also minimizes operational redundancies, ultimately leading to substantial financial benefits. The chapter concludes with future directions and challenges in the adoption of QAI technologies in mainstream business practices.

Fields of Study & Subjects

Quantum Computing Algorithms and Architecture Impact of AI and Big Data on Business and Society Artificial Intelligence Applications

Publication details

Journal / source
Advances in computational intelligence and robotics book series
Pages
87–124
Publication date
13 March 2026
Language
EN
Document type
Book chapter