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Quantum AI: Merging Quantum Computing and Artificial Intelligence

Book Chapter

Authors: Vijaya Kittu Manda; Madhu Bhukya; Lela Mirtskhulava

DOI: https://doi.org/10.70593/978-93-7185-732-1

Book Name: Quantum Artificial Intelligence Applications in Industry 5.0

ISBN: Book (Paperback): 978-93-7185-948-6; eISBN: 978-93-7185-732-1

Publisher: Deep Science Publishing

Editor(s): Dr. Dina Darwish

Book Chapter Number: 2

Publication Date: March 13, 2026

Pages: Pages 25 - 47 (22 pages)

Book Link on Publisher Website

Abstract: Quantum Computing (QC) and Artificial Intelligence (AI) represent two transformative technologies. Their convergence, termed Quantum AI (QAI), promises to overcome the computational limitations of classical AI and enable advanced applications in Industry 5.0. This work discusses the potential of integrating quantum principles - superposition, entanglement, and tunneling - with AI systems to achieve exponential speedups in complex tasks. Classical AI has several bottlenecks. Quantum-enhanced approaches, particularly Quantum Machine Learning (QML), incorporate hybrid quantum-classical architectures, such as Variational Quantum Circuits (VQCs) and Quantum Neural Networks (QNNs), and algorithms such as the Variational Quantum Eigensolver (VQE) and the Quantum Approximate Optimization Algorithm (QAOA) to address these challenges. These frameworks offer real-time optimization, hyper-personalization, resilient supply chains, and human-centric cognitive systems, aligning with Industry 5.0’s emphasis on human-machine collaboration and sustainability. Despite promising frameworks (e.g., Qiskit, PennyLane), current Noisy Intermediate-Scale Quantum (NISQ) hardware imposes limitations like noise, barren plateaus, data encoding bottlenecks, and scalability issues. The work highlights the need for fault-tolerant systems, quantum-safe security for Industrial IoT, and proactive ethical governance to mitigate risks, including the emerging “Quantum Divide.”

Keywords: Quantum Artificial Intelligence, Quantum Machine Learning, Human-Machine Collaboration, Variational Quantum Algorithms, Hybrid Quantum-Classical Computing, Quantum Neural Networks

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