The Europe Quantum AI Market would witness market growth of 34.6% CAGR during the forecast period (2024-2031).
The Germany market dominated the Europe Quantum AI Market by Country in 2023, and would continue to be a dominant market till 2031; thereby, achieving a market value of $123.1 million by 2031. The UK market is exhibiting a CAGR of 33.5% during (2024 - 2031). Additionally, the France market would experience a CAGR of 35.7% during (2024 - 2031).
A subset of AI that concentrates on the development of algorithms that enable computers to learn from and make predictions based on data is machine learning, which is one of the most promising applications of this. Machine learning models, particularly deep learning models, require substantial computational resources to train and optimize. As the complexity of these models increases, so does the demand for processing power, often leading to bottlenecks in performance. This has the potential to resolve these obstacles by offering the computational power necessary to train more complex and expansive models in a fraction of the time required by classical systems.
Moreover, traditional machine learning tasks, including clustering, regression, and classification, have also been improved by quantum machine learning (QML). For instance, QML algorithms are capable of processing enormous datasets with numerous features and greater efficiency than classical algorithms, resulting in more precise and resilient models in classification tasks. Specifically, this is advantageous in sectors such as healthcare, where AI algorithms classify medical images or forecast disease outcomes by analyzing patient data. Quantum-enhanced classification models can improve diagnostic accuracy and help healthcare providers make more informed decisions. Similarly, QML algorithms can more accurately model complex relationships between variables in regression tasks, leading to better predictions and insights in economics, weather forecasting, and market analysis.
Government initiatives, strong research infrastructures, and strategic collaborations between academia and industry drive the demand for this across Europe. The German government's Quantum Computing Roadmap, part of the broader High-Tech Strategy 2025, outlines a vision for Germany to become a leader in quantum technologies, emphasizing this. The ‘Framework Programme Quantum Technologies - from the Fundamentals to the Market’ was adopted by the Cabinet in September 2018. The funding volume amounts to 860 million euros in the current legislative term. This funding supports various initiatives, including developing quantum processors and these applications for automotive, manufacturing, and logistics industries. Thus, the collaborative environment fostered by these initiatives ensures that Europe remains at the cutting edge of quantum AI research and application.
Based on Deployment Mode, the market is segmented into On-premises and Cloud based. Based on Application, the market is segmented into Machine learning & Optimization, Simulation and Modeling, and Cryptography & Security. Based on Component, the market is segmented into Hardware, Software, and Services. Based on countries, the market is segmented into Germany, UK, France, Russia, Spain, Italy, and Rest of Europe.
The Germany market dominated the Europe Quantum AI Market by Country in 2023, and would continue to be a dominant market till 2031; thereby, achieving a market value of $123.1 million by 2031. The UK market is exhibiting a CAGR of 33.5% during (2024 - 2031). Additionally, the France market would experience a CAGR of 35.7% during (2024 - 2031).
A subset of AI that concentrates on the development of algorithms that enable computers to learn from and make predictions based on data is machine learning, which is one of the most promising applications of this. Machine learning models, particularly deep learning models, require substantial computational resources to train and optimize. As the complexity of these models increases, so does the demand for processing power, often leading to bottlenecks in performance. This has the potential to resolve these obstacles by offering the computational power necessary to train more complex and expansive models in a fraction of the time required by classical systems.
Moreover, traditional machine learning tasks, including clustering, regression, and classification, have also been improved by quantum machine learning (QML). For instance, QML algorithms are capable of processing enormous datasets with numerous features and greater efficiency than classical algorithms, resulting in more precise and resilient models in classification tasks. Specifically, this is advantageous in sectors such as healthcare, where AI algorithms classify medical images or forecast disease outcomes by analyzing patient data. Quantum-enhanced classification models can improve diagnostic accuracy and help healthcare providers make more informed decisions. Similarly, QML algorithms can more accurately model complex relationships between variables in regression tasks, leading to better predictions and insights in economics, weather forecasting, and market analysis.
Government initiatives, strong research infrastructures, and strategic collaborations between academia and industry drive the demand for this across Europe. The German government's Quantum Computing Roadmap, part of the broader High-Tech Strategy 2025, outlines a vision for Germany to become a leader in quantum technologies, emphasizing this. The ‘Framework Programme Quantum Technologies - from the Fundamentals to the Market’ was adopted by the Cabinet in September 2018. The funding volume amounts to 860 million euros in the current legislative term. This funding supports various initiatives, including developing quantum processors and these applications for automotive, manufacturing, and logistics industries. Thus, the collaborative environment fostered by these initiatives ensures that Europe remains at the cutting edge of quantum AI research and application.
Based on Deployment Mode, the market is segmented into On-premises and Cloud based. Based on Application, the market is segmented into Machine learning & Optimization, Simulation and Modeling, and Cryptography & Security. Based on Component, the market is segmented into Hardware, Software, and Services. Based on countries, the market is segmented into Germany, UK, France, Russia, Spain, Italy, and Rest of Europe.
List of Key Companies Profiled
- Amazon Web Services, Inc. (Amazon.com, Inc.)
- Microsoft Corporation
- Google LLC
- IBM Corporation
- Fujitsu Limited
- Intel Corporation
- Toshiba Corporation
- Rigetti Computing, Inc.
- D-Wave Systems Inc.
- Hitachi Digital Services, LLC (Hitachi Ltd.)
Market Report Segmentation
By Deployment Mode
- On-premises
- Cloud based
By Application
- Machine learning & Optimization
- Simulation and Modeling
- Cryptography & Security
By Component
- Hardware
- Software
- Services
By Country
- Germany
- UK
- France
- Russia
- Spain
- Italy
- Rest of Europe
Table of Contents
Chapter 1. Market Scope & Methodology
Chapter 2. Market at a Glance
Chapter 3. Market Overview
Chapter 4. Competition Analysis - Global
Chapter 5. Europe Quantum AI Market by Deployment Mode
Chapter 6. Europe Quantum AI Market by Application
Chapter 7. Europe Quantum AI Market by Component
Chapter 8. Europe Quantum AI Market by Country
Chapter 9. Company Profiles
Companies Mentioned
- Amazon Web Services, Inc. (Amazon.com, Inc.)
- Microsoft Corporation
- Google LLC
- IBM Corporation
- Fujitsu Limited
- Intel Corporation
- Toshiba Corporation
- Rigetti Computing, Inc.
- D-Wave Systems Inc.
- Hitachi Digital Services, LLC (Hitachi Ltd.)
Methodology
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