Quantum Machine Learning Market Research Report – Segmented By Component (Hardware, Software, Services); By deployment ( On-Premise, Cloud-Based); By End-User (Healthcare, Banking, Financial Services and Insurance (BFSI), Automotive, Researchers, Energy and Utilities, Chemical, Manufacturing, Others); and Region - Size, Share, Growth Analysis | Forecast (2023 – 2030)

Global Quantum Machine Learning Market Size (2023 – 2030)

The Quantum Machine Learning Market was valued at USD 613 million in 2022 and is projected to reach USD 5000.43 million by 2030. The market is anticipated to expand at a CAGR of 30% over the forecast period. The market for quantum machine learning is expanding due to the rising need for advanced computing power. Growing demand for Software-as-a-Service (SaaS) business models, rising data centre workloads, and the difficulty of processor design in traditional binary computing systems are the main reasons propelling the global quantum machine learning market.

Quantum Machine Learning Market

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The powerful computer technology is known as "quantum computing" is based on quantum theory and quantum mechanics. The quantum computer has been used for quantum computing, which is based on quantum physics principles. Regarding speed, bits, and data, it is distinct from classical computing. While traditional computing only employs the two bits 0 and 1, quantum computing uses all possible states between 0 and 1, which promotes superior outcomes and rapid processing. Finding the best answer to a challenging problem typically involves using quantum computing to compare several options. It has been employed in several industries, including chemicals, utilities, healthcare & pharmaceuticals, and defence. Applications including machine learning, cryptography, algorithms, quantum simulation, quantum parallelism, and others employ quantum computing. Since quantum computing has the potential to speed up pharmaceutical research and increase the precision of the atmospheric models to explain climate change and its effect, it will help improve solutions to demanding different fields. Additionally, batteries with greater energy densities, more efficient catalytic and synthetic processes, and favourable strength to weight ratios of the material all assist the automotive, electronics, and aerospace sectors. Quantum Machine Learning is also helpful in scheduling, planning, distribution, and routing of production for industrial products; chemical and enzyme design for the chemical industry; trading strategies, portfolio optimization, asset pricing, fraud detection, and market simulation for the BFSI sector. As a result of quantum computing's ability to analyse data quickly and offer endless storage, several sectors are embracing and developing the technology. Additionally, due to the enormous volumes of complicated data they contain, significant fields like optimization, simulation, data modelling & analysis, and machine & deep learning, in particular, have a strong need for high-performance computing.


The global growth of computer services was significantly impacted by the COVID-19 pandemic. Due to the COVID 19 epidemic, demand for quantum computing ETFs (exchange-traded funds) and equities has increased in the majority of countries since the global shutdown. Many governments have increased their spending on pharmaceuticals and healthcare. The adoption of cutting-edge technology, like quantum computing stocks, is also a top goal for businesses in this field. Utilizing computational technology, scientists may create highly precise and individually tailored medicinal and diagnostic systems. Furthermore, potential uses for quantum machine learning computer services in vaccine development may be seen given the impact of post-COVID-19 on society, the economy, and healthcare. Due to its ability to address larger problem spaces with more accuracy, quantum machine learning will play a significant role in these domains, and this is further expected to fuel the market's expansion. The growing reliance on digital computing solutions is anticipated to have a beneficial influence on this market post the COVID-19 pandemic. The adoption of work-from-home policies and digitalization may result from the worrisome increase in COVID patients and the appearance of novel viral varieties. Acceptance of cutting-edge software and rapid digitalization might increase the adoption and deployment of quantum machine learning solutions. Additionally, it is anticipated that e-growing commerce's popularity would help the market expansion.


The banking and financial industries were early adopters of quantum computing which is positively influencing the market development

In the banking and finance services sector, which is focused on accelerating trade activities, transactions, and data processing significantly, quantum machine learning is gaining popularity. The simulation and automation of processes are one of the key possible uses of quantum machine learning computing. The identification of a better and more effective method to control financial risks is aided by quantum computing. If conventional computers are employed in financial institutions, the processing time and costs of high-quality solutions may rise exponentially, but quantum computers may perform quick operations at reduced costs, leading to cost reductions and new prospects for income creation.

The rise in investments in quantum machine learning computing technology is fueling the growth

To apply various optimization and simulation tactics using quantum computers, several government agencies involved in the worldwide space and military industries are spending more and more on the development of quantum computing technology. Governments from many different nations across the world are investing a sizable amount of money to assist their research institutions in the advancement of quantum computing technology. China is making major investments in research and development projects using quantum computing. The governments of the United States, Australia, and the EU nations are moving forward with quantum computing efforts.


The growth of the Quantum machine learning market is impeded by stability issues and error correction

Commercializing quantum machine learning computers is a challenging, complex undertaking since qubits are delicate and easily disrupted by changes in ambient temperature, noise, and frequency; as a result, it has been challenging to maintain their quantum mechanical state for a long period. The elliptic curve digital signature technique (ECDSA), which is presently not quantum-safe, is also utilised in several applications based on digital ledgers. These services' strength also comes from their ability to store a complex state in a single bit. Quantum systems are challenging to build, test, and design due to this aspect as well. Bits usually need to operate at extremely low temperatures because of the fragility of quantum states. Production must be precise.




Market Size Available

2022 - 2030

Base Year


Forecast Period

2023 - 2030



Segments Covered

By Component, Deployment, End-User, and Region

Various Analyses Covered

Global, Regional & Country Level Analysis, Segment-Level Analysis, DROC, PESTLE Analysis, Porter’s Five Forces Analysis, Competitive Landscape, Analyst Overview on Investment Opportunities

Regional Scope

North America, Europe, APAC, Latin America, Middle East & Africa

Key Companies Profiled


This research report on the Quantum Machine Learning Market has been segmented and sub-segmented based on Component, By Deployment, By End-User and By Region.


  • Hardware

  • Software

  • Services

Based on components, the Quantum Machine learning market is segmented into hardware, software and services. The hardware segment is predicted to expand significantly over the forecast period since it is utilised extensively in the BFSI industry to significantly speed up business operations, activities, and data processing. Additionally, it assists in the development of a system for controlling financial risks that is more effective and efficient. Additionally, when using conventional classical computers in financial institutions, processing times and costs for high-quality solutions can increase exponentially. In contrast, the software and services sector is anticipated to expand quickly due to an increase in startups globally and significant expenditures on computing-related research and development. The use of this information technology in simulation, deep learning, and optimization applications has led to lower operating costs and more effective operations across a range of industries.


  • On-Premise

  • Cloud-Based

Based on deployment, the Quantum Machine learning market is segmented into On-Premise and Cloud-Based. Throughout the projected period, cloud-based deployment is anticipated to rule the market. With the development of more potent systems, the need for cloud-based computing goods and services is projected to increase. It is anticipated that users paying for access to noisy intermediate-scale quantum (NISQ) systems that can solve practical problems would provide a sizable revenue stream for service providers. Companies that provide cloud services gain from the equipment's short lifespan and quick technological evolution. The flexibility of access offered to users is another factor contributing to the growth in the popularity of cloud-based quantum machine learning computing systems and services. It seems doubtful that portable quantum computers will exist in the foreseeable future. Customers may access numerous gadgets and simulations through the cloud from their laptops.


  • Healthcare

  • Banking, Financial Services and Insurance (BFSI)

  • Automotive

  • Researchers

  • Energy and Utilities

  • Chemical

  • Manufacturing

  • Others

Based on the end-users, the Quantum Machine learning market is segmented into Healthcare, Banking, Financial Services and Insurance (BFSI), Automotive, Researchers, Energy and Utilities, chemicals and Manufacturing among Others. During the projection period, BFSI is anticipated to have the largest market share. Quantum machine learning enables users to handle complex operations needing historical data with the aid of quantum algorithms and computers, resulting in accurate outcomes. Additionally, HFT (High-Frequency Trading) and ADM (Automated Decision Making) use Quantum machine learning services since they need a lot of computer power to handle data in real-time with few mistakes. During the projected period for quantum machine learning to compute, considerable revenue growth is anticipated in the research and healthcare sectors. In the research and healthcare sectors, computing services are used to handle a range of applications, including accelerating diagnosis, tailoring treatment, and optimising pricing. These might enable several disruptive use cases for providers and health insurance. Machine learning techniques with quantum enhancement are very appealing to the industry.


  • North America

  • Europe

  • The Asia Pacific

  • Latin America

  • The Middle East

  • Africa

By region, the Quantum Machine Learning Market is grouped into North America, Europe, Asia Pacific, Latin America, The Middle East and Africa.  The North American market emerged as the market leader in 2021 with a revenue of USD 171.1 million. Due to the early adoption of cutting-edge technology and a highly competitive environment, North America has experienced significant expansion in the overall market. The region's adoption of quantum computing is attributable to the prevalence of important market participants. Key suppliers have been prompted to create sophisticated services as a result of end consumers' preparedness to accept evolving technology. Due to the increase in startups, Europe is predicted to experience tremendous growth. Additionally, the area anticipated propelling the growth of the market and technology is seeing a boost in cloud-based technology adoption, regulatory settings, and digital government activities.

The Asia Pacific region has significant industries in banking and finance, healthcare, and chemicals. Japan, China, and South Korea are the region's main producers of electronic devices such as game consoles, computers, and cellphones. There is a need to address problems with simulation, optimization, and machine learning applications across various industries. Large and medium-sized businesses in the area are gaining from the rapid development of APAC's expanding economies and the greater usage of new technology in the industrial sector. The Asia Pacific is therefore experiencing a surge in demand for these computing services and solutions.


Some of the major players operating in the Quantum Machine Learning Market include:

  • IBM corporation

  • D-Wave sytems










INVESTMENT – To develop commercial space-based QKD based on technology created at the National University of Singapore's Centre for Quantum Technologies, Singapore-based firm SpeQtral obtained USD 8.3 million in investment in December 2021. 

COLLABORATION- Classiq and NTT DATA collaborated in December 2021 to implement algorithms for credit risk analysis. Additionally, the Classiq software will allow users to select algorithms that will work with other quantum hardware platforms in the future, providing a potential lender with an answer that is more precise or quick.

INVESTMENT- Quantum control solution company Q-CTRL announced a Series B investment round of USD 25 million in November 2021, with Airbus Ventures serving as the lead investor. With the aid of quantum sensors for acceleration, gravity, and magnetic fields, this invention will enable Q-CTRL to create new data as a service market.

PRODUCT LAUNCH- The public release of Amazon Bracket, a fully managed Amazon Web Services (AWS) service that offers a research environment for investigating and creating new quantum algorithms, was announced by Amazon in August 2020. Customers may test and debug algorithms on simulated quantum computers operating in the cloud using Bracket, which was introduced in preview form in December. 

PRODUCT LAUNCH- Google introduced a simulator in December 2020 to help scientists create quantum algorithms. The dominant search engine has unveiled a brand-new webpage to assist users in utilising Qasim and other open-source quantum technology. Google's tools, research programmes, teaching resources, up-to-date publications, and research archives are all accessible to researchers via the

Chapter 1. Quantum Machine Learning Market – Scope & Methodology

1.1. Market Segmentation

1.2. Assumptions

1.3. Research Methodology

1.4. Primary Sources

1.5. Secondary Sources

Chapter 2. Quantum Machine Learning Market – Executive Summary

2.1. Market Size & Forecast – (2023 – 2030) ($M/$Bn)

2.2. Key Trends & Insights

2.3. COVID-19 Impact Analysis

       2.3.1. Impact during 2023 - 2030

       2.3.2. Impact on Supply – Demand

Chapter 3. Quantum Machine Learning Market – Competition Scenario

3.1. Market Share Analysis

3.2. Product Benchmarking

3.3. Competitive Strategy & Development Scenario

3.4. Competitive Pricing Analysis

3.5. Supplier - Distributor Analysis

Chapter 4. Quantum Machine Learning Market Entry Scenario

4.1. Case Studies – Start-up/Thriving Companies

4.2. Regulatory Scenario - By Region

4.3 Customer Analysis

4.4. Porter's Five Force Model

       4.4.1. Bargaining Power of Suppliers

       4.4.2. Bargaining Powers of Customers

       4.4.3. Threat of New Entrants

       4.4.4. Rivalry among Existing Players

       4.4.5. Threat of Substitutes

Chapter 5. Quantum Machine Learning Market - Landscape

5.1. Value Chain Analysis – Key Stakeholders Impact Analysis

5.2. Market Drivers

5.3. Market Restraints/Challenges

5.4. Market Opportunities

Chapter 6. Quantum Machine Learning Market – By Component

6.1. Hardware

6.2. Software

6.3. Services

Chapter 7. Quantum Machine Learning Market – By Deployment

7.1. On-Premise

7.2. Cloud-Based

Chapter 8. Quantum Machine Learning Market – By End-use

8.1. Healthcare

8.2. Banking, Financial Services and Insurance (BFSI)

8.3. Automotive

8.4. Researchers

8.5. Energy and Utilities

8.6. Chemical

8.7. Manufacturing

8.8. Others

Chapter 9. Quantum Machine Learning Market- By Region

9.1. North America

9.2. Europe

9.3. Asia-Pacific

9.4. Latin America

9.5. The Middle East

9.6. Africa

Chapter 10. Quantum Machine Learning Market – key players

10.1. IBM corporation

10.2. D-Wave sytems



10.5. RIGETTI & CO, INC.




10.9. XANADU





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