The Opportunities and Challenges in Integrating AI with Quantum Computing

The convergence of Artificial Intelligence (AI) and Quantum Computing (QC) marks a potentially transformative technological frontier. This study explores the synergistic integration of these fields, analyzing the landscape of opportunities and challenges arising from their combination. Quantum comp...

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Main Authors: Tomasz Słapczyński, Marlena Stradomska
Format: Article
Language:English
Published: University of Applied Sciences in Bielsko-Biała 2025-06-01
Series:Zeszyty Naukowe Wyższej Szkoły Finansów i Prawa w Bielsku-Białej
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Online Access:https://asej.eu/index.php/asej/article/view/850
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author Tomasz Słapczyński
Marlena Stradomska
author_facet Tomasz Słapczyński
Marlena Stradomska
author_sort Tomasz Słapczyński
collection DOAJ
description The convergence of Artificial Intelligence (AI) and Quantum Computing (QC) marks a potentially transformative technological frontier. This study explores the synergistic integration of these fields, analyzing the landscape of opportunities and challenges arising from their combination. Quantum computing offers the promise to enhance AI by overcoming computational bottlenecks and enabling novel algorithms, particularly within machine learning and optimization. This analysis reveals significant opportunities in areas like accelerated machine learning, tackling intractable problems, and processing quantum data. However, substantial challenges currently impede progress, primarily due to limitations in Noisy Intermediate-Scale Quantum (NISQ) hardware, algorithmic complexities in demonstrating practical quantum advantage, and practical hurdles in implementation and interdisciplinary expertise. Despite these challenges, the synergistic potential of AI-QC integration remains immense, promising a paradigm shift in computational capabilities with the continued advancement of both fields, ultimately poised to revolutionize science, industry, and society
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publishDate 2025-06-01
publisher University of Applied Sciences in Bielsko-Biała
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series Zeszyty Naukowe Wyższej Szkoły Finansów i Prawa w Bielsku-Białej
spelling doaj-art-1064b154560543d2b6d57e185c6064b92025-08-20T03:14:35ZengUniversity of Applied Sciences in Bielsko-BiałaZeszyty Naukowe Wyższej Szkoły Finansów i Prawa w Bielsku-Białej2543-91032543-411X2025-06-0129210.19192/wsfip.sj2.2025.8The Opportunities and Challenges in Integrating AI with Quantum Computing Tomasz Słapczyński0Marlena Stradomska1Maria Curie-Sklodowska University in LublinMaria Curie Sklodowska University Lublin The convergence of Artificial Intelligence (AI) and Quantum Computing (QC) marks a potentially transformative technological frontier. This study explores the synergistic integration of these fields, analyzing the landscape of opportunities and challenges arising from their combination. Quantum computing offers the promise to enhance AI by overcoming computational bottlenecks and enabling novel algorithms, particularly within machine learning and optimization. This analysis reveals significant opportunities in areas like accelerated machine learning, tackling intractable problems, and processing quantum data. However, substantial challenges currently impede progress, primarily due to limitations in Noisy Intermediate-Scale Quantum (NISQ) hardware, algorithmic complexities in demonstrating practical quantum advantage, and practical hurdles in implementation and interdisciplinary expertise. Despite these challenges, the synergistic potential of AI-QC integration remains immense, promising a paradigm shift in computational capabilities with the continued advancement of both fields, ultimately poised to revolutionize science, industry, and society https://asej.eu/index.php/asej/article/view/850Quantum AIQuantum Machine Learning (QML)Hybrid Quantum-Classical ComputingComputational AdvantageNISQ Era Challenges
spellingShingle Tomasz Słapczyński
Marlena Stradomska
The Opportunities and Challenges in Integrating AI with Quantum Computing
Zeszyty Naukowe Wyższej Szkoły Finansów i Prawa w Bielsku-Białej
Quantum AI
Quantum Machine Learning (QML)
Hybrid Quantum-Classical Computing
Computational Advantage
NISQ Era Challenges
title The Opportunities and Challenges in Integrating AI with Quantum Computing
title_full The Opportunities and Challenges in Integrating AI with Quantum Computing
title_fullStr The Opportunities and Challenges in Integrating AI with Quantum Computing
title_full_unstemmed The Opportunities and Challenges in Integrating AI with Quantum Computing
title_short The Opportunities and Challenges in Integrating AI with Quantum Computing
title_sort opportunities and challenges in integrating ai with quantum computing
topic Quantum AI
Quantum Machine Learning (QML)
Hybrid Quantum-Classical Computing
Computational Advantage
NISQ Era Challenges
url https://asej.eu/index.php/asej/article/view/850
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