American Journal of Advanced Multidisciplinary Research and Innovation

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Quantum Computing and Artificial Intelligence: The Future of Intelligent Computing

Author(s) Amy Finkelstein
Country United States
Abstract Quantum Computing (QC) and Artificial Intelligence (AI) represent two of the most transformative technologies of the twenty-first century. Individually, Artificial Intelligence has revolutionized intelligent decision-making, automation, predictive analytics, and human–computer interaction, while Quantum Computing promises unprecedented computational capabilities by exploiting the principles of quantum mechanics, including superposition, entanglement, and quantum interference. The convergence of Quantum Computing and Artificial Intelligence, commonly referred to as Quantum Artificial Intelligence (QAI), has the potential to solve computational problems that remain intractable for classical computers. Applications include accelerated machine learning, complex optimization, molecular simulation, cryptography, financial modeling, intelligent robotics, precision medicine, climate modeling, logistics, and advanced scientific discovery.
This study explores the integration of Quantum Computing and Artificial Intelligence as the future of intelligent computing through a multidisciplinary perspective. Using a qualitative and analytical research methodology based on secondary data from computer science, quantum information science, mathematics, engineering, healthcare, finance, and information systems literature, the study examines the evolution of quantum technologies, AI methodologies, quantum machine learning algorithms, industrial applications, implementation challenges, governance frameworks, and future research directions. Particular emphasis is placed on quantum-enhanced optimization, hybrid quantum–classical computing, explainable quantum AI, cybersecurity, ethical governance, and sustainable technological innovation.
The findings indicate that the convergence of Quantum Computing and AI can dramatically accelerate computational efficiency, improve optimization capabilities, enhance intelligent automation, and enable discoveries across multiple scientific disciplines. However, significant challenges remain, including hardware scalability, quantum error correction, algorithm development, cybersecurity implications, high implementation costs, workforce skill shortages, and ethical governance. The study concludes that hybrid quantum–AI ecosystems, supported by responsible innovation and interdisciplinary collaboration, will play a central role in the future of intelligent computing.
Keywords Quantum Computing, Artificial Intelligence, Quantum Machine Learning, Intelligent Computing, Hybrid Computing, Quantum Algorithms, Future Technologies, Industry 5.0.
Field Engineering
Published In Volume 3, Issue 4, July-August 2021
Published On 2021-07-21
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