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Machine Learning (ML) Market Size, Share & COVID-19 Impact Analysis, By Component (Solution, and Services), By Enterprise Size (SMEs, and Large Enterprises), By Deployment (Cloud and On-premise), By Industry (Healthcare, Retail, IT and Telecommunication, BFSI, Automotive and Transportation, Advertising and Media, Manufacturing, and Others), and Regional Forecast, 2021-2028

Region : Global | Format: PDF | Report ID: FBI102226



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The global machine learning market size was USD 11.33 billion in 2020. The global impact of COVID-19 has been unprecedented and staggering, with machine learning solutions/services witnessing a positive demand shock across all regions amid the pandemic. Based on our analysis, the global market exhibited a significant growth of 36.2% in 2020 as compared to year-on-year growth during 2017-2019. The market is projected to grow from USD 15.50 billion in 2021 to USD 152.24 billion in 2028 at a CAGR of 38.6% in the 2021-2028 period. The steady rise in CAGR is attributable to this market’s demand and growth, returning to pre-pandemic levels once the pandemic is over.

In the global effort to attenuate the spread of novel Coronavirus, several countries have adopted quarantine measures and social distancing policies to mitigate the impact of the pandemic. The developers and researchers intend to use ML tools to analyze the effects of these measures.

  • For instance, in April 2020, the Massachusetts Institute of Technology researchers developed a model that uses the data from the COVID-19 pandemic. The model leverages machine intelligence algorithms to determine or predict the spread of the virus and the efficacy of quarantine measures. Such advancements are likely to surge the demand for advanced machine intelligence capabilities.

Advancements in deep learning and integration of machine intelligence capabilities with analytics-driven solutions are expected to be the growing market trend. Substantial investments in artificial intelligence (AI) and the advent of self-driving cars are some of the factors that influence market growth. These factors are driving the machine learning market growth across industries and regions.

COVID-19 Impact

COVID-19 Pandemic Across the Globe to Create Unprecedented Market Opportunities for the Companies

The COVID-19 pandemic has had a significant effect on countries' health, financial, and social systems. Individuals can profit from understanding and coping with their mental, psychological, and social well-being if knowledge of individual-level susceptibility factors is accessible.

The application of artificial intelligence technology is likely to help combat the COVID-19 pandemic. Several countries are using population surveillance methods to track and trace COVID-19 cases. For example, in South Korea, researchers use surveillance camera footage, geo-location data to track coronavirus patients. Using this data, the data scientists leverage machine intelligence algorithms to predict the location of the next outbreak and inform the responsible authorities, helping to track the disease in real-time. Such active initiatives are likely to surge the demand for machine intelligence solutions in the upcoming period.


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Advancements in Deep Learning to Push the Market Towards a Higher Growth Trajectory

The field of machine intelligence is experiencing exponential growth across the globe. Deep learning is a subset of ML in artificial intelligence (AI) technology. It leverages the hierarchical level of artificial neural networks (ANN) to carry out the process of machine learning. The global market is expected to gain traction owing to the advancements in deep learning algorithms.

Many companies are strengthening their deep learning capabilities to drive innovation. For instance, in November 2019, Panasonic Corporation announced its application programming interface (API) for facial recognition technology incorporated with deep learning capabilities.

Integration of Machine Intelligence with Analytics-driven Solutions to be a Growing Market Trend

Retail analytics has witnessed significant growth in recent years. Many e-commerce companies such as Amazon, Alibaba, and eBay are leveraging advanced data analytics solutions to boost their sales and enhance customer experience. Research and development in speech and voice recognition technology have led to the emergence of cognitive speech coding techniques using ML paradigms.

The adoption of machine learning in security analytics will be a key trend as companies tend to adopt more sophisticated security frameworks. With an enormous volume of data being produced and shared across multiple networks, tracking and evaluating possible cyber risks and attacks present a significant challenge for cyber experts. Further, as cyber threats grow more common and advanced, Machine learning algorithms help companies and security teams to anticipate, track, and recognize cyber attacks more rapidly. Thus, integrating advanced learning capabilities into analytics-driven solutions is likely to be a growing market trend.


Substantial Investments in Artificial Intelligence (AI) to Drive the Market in Long-Term

The commercial applications of AI are increasing in advanced and emerging economies. As a result, there is an intensified competition between the market players to fund, develop, and acquire artificial intelligence technology startups. For instance, in May 2020, Intel Corporation announced an investment of USD 132 million in 11 disruptive technology startups such as California-based Anodot, which leverages ML to drive autonomous business monitoring. Similarly, Hypersonix, a provider of AI-powered autonomous analytics platforms, KFBIO, the digital pathology system provider and Xsight Labs develop innovative technology for machine intelligence, data analytics, and disaggregated storage. Such heavy investments would ensure to drive the global market in the upcoming years.

Advent of Self-Driving Cars to Augment the Need for Advanced Learning Solutions

Self-driving cars have gained tremendous popularity in recent years. The advancements in artificial intelligence technology and the Internet of Things (IoT) have paved the way for driverless cars. Machine learning is a vital component of the centralized electronic control unit (ECU) in a self-driving car. Real-time monitoring of the surrounding environment and predicting possible changes in the environment is one of ML algorithms' primary functions in self-driving cars.

ML algorithms such as supervised learning, unsupervised learning, pattern recognition algorithms, decision matrix algorithms, among others, are leveraged into the functioning of self-driving cars. For example, Waymo LLC is an autonomous driving technology development company headquartered in California. The U.S. uses categorical machine intelligence technology to classify and detect different types of road features and objects. By incorporating advanced ML algorithms, the company intends to expand to more cities to encounter new scenarios and objects. These factors are likely to fuel the demand for intelligent retrieval algorithms, thereby driving the market.


Increasing Emphasis on Data Privacy to Restrict the Market Growth

Deepfakes posed by AI-enabled fake content are suspected to be a national security threat. However, the idea of AI licenses can overcome this constraint. For instance, Responsible AI licenses (RAIL) enable the software developer to publish open-source ML software with a license. This mitigates the risk of the software being used illegally.

Also, machine intelligence in robotic automation processes is exposed to fraud and undesired use cases which may hinder the market growth. To prevent the misuse of robots, governments across the regions are taking preventive measures. For instance, in September 2018, California approved a bill namely ‘California B.O.T. Act of 2018’. The law would criminalize the use of bots to interact with California's citizens if the bot intends to mislead the person.


By Component Analysis

Machine Learning Solutions to Account for Major Market Share

By component, the global market is segmented into solutions and services.

The solution segment has captured maximum market share in 2020 and is expected to maintain its dominance in the forthcoming era. The solutions provided by the market players include IBM Corporation’s Watson Machine learning, Oracle ML, Microsoft Corporation’s Azure ML among others. These solutions help data scientists and researchers to accelerate the deployment of artificial intelligence and ML. Machine-learning-as- a service is expected to be a growing market trend in the coming years.

Professional and managed services are considered under the services segment. The services are anticipated to witness significant growth during the forecast period. These services help industries in making informed decisions, actionable strategies, enhance operation workflow, end-to-end risk, and compliance management capabilities.

By Enterprise Size Analysis

Small and Mid-Sized Enterprises to Increase their Tech Spending’s to Deploy AI and ML Technologies

By enterprise size, the global market is bifurcated into small and mid-sized enterprises and large enterprises.

Large enterprises segment accounted for the largest machine learning market share in 2020. This is attributed to the growing implementation of technology such as artificial intelligence and data science to introduce quantitative insights into enterprise operations. Large companies are working on harnessing deep learning, artificial learning, and optimization of decisions in order to provide high market services. Several large enterprises have been extensively adopting ML  to derive required knowledge from large data amounts and predict the outcomes of different problems.

Small and mid-sized enterprises are estimated to exhibit a significant growth rate during the forecast period. AI and ML are expected to be the key technologies that will enable the SMEs to reduce ICT investments and access digital resources. Large enterprises are likely to hold the major market share. As a result of rising digitization and increased cyber threats to sensitive business information and data, rapidly evolving and highly active SMEs have increased their adoption of these technologies and services across the globe.

By Deployment Analysis

Increasing Demand for Cloud-Based Solutions to Aid Growth

By deployment, the market has been classified into the cloud and on-premise.

The market players offer machine intelligence solutions that can be deployed on the cloud or on-premise. For instance, Alphabet, Inc. provides Google Cloud. The Google cloud offers a comprehensive toolset regarding ML and AI. Similarly, BigML offers on-premise deployments for enterprises that wish to configure, maintain, and manage their installations within the enterprise. The cloud deployments are expected to witness a remarkable growth rate during the forecast period. Flexibility, automatic software upgrades, disaster management via cloud-based backup systems, and enhanced efficiency are a few of the key advantages that have prompted the implementation of cloud-based delivery models for deep learning software solutions and services.

The on-premises segment captured a significant market share in 2020. This segment's growth would occur on account of the large calculation capacity and data security compliance it offers.

By Industry Analysis

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Healthcare Industry to Witness a Remarkable Market Growth

The industries working with large amounts of data leverage ML technology to glean real-time insights from the data. The real-time insights enable the industries to gain more advantage over competitors and work more efficiently.

In the pre-COVID scenario, the advent of wearable devices and sensors that are used to assess patients’ health in real-time has surged the demand for machine intelligence applications in the healthcare industry. The technology helps the medical experts to identify trends and analyze data to improve diagnosis and treatment. However, the outbreak of novel Coronavirus has tractioned the applications of artificial learning technology across the sector.

Banks and other financial businesses leverage machine intelligence technology to prevent fraud and identify important insights in data. E-Commerce has proved to be a major driver for retail trade business practices. Retailers rely on machine intelligence to capture data, analyze it, and leverage it to offer personalized shopping experiences to customers. These are some of the aspects that drive the demand for this technology in the financial and retail industries.

In the pre-COVID period, the manufacturing industry had been demonstrating an impressive adoption of artificial intelligence technology. Industrial Internet of Things (IIoT), smart factories including smart robotics, intelligent logistics, autonomous delivery using drones, intelligent inventory management are some of the strong use cases of ML in the manufacturing industry.

Automotive and transportation are projected to witness significant growth in the coming years. Research & development in self-driving cars, autonomous transportation drive the demand for advanced solutions. In the advertising and media industry, proliferation of over-the-top (OTT) services has influenced the OTT providers such as Netflix, Hotstar, and Amazon.com among others to deploy deep learning and machine intelligence to gain deep customer insights.

Further, machine intelligence has gained importance in the education sector owing to advanced programs such as Education 3.0.  In the energy and utilities industry, prediction of energy consumption is the most popular use case of ML technology. Smart grid distribution drives the need for advanced algorithms in the sector.


North America Machine Learning Market Size, 2020 (USD Billion)

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Geographically, the market is segmented across five major regions, namely, North America, Europe, Asia Pacific, the Middle East & Africa, and Latin America.

North America captured the maximum market share in 2020. The presence of major R&D investors such as IBM Corporation, Amazon.com, and Oracle Corporation expands the market size across the region. Moreover, high investments and availability of established IT infrastructure are expected to drive the market growth in North America. For instance, the defense advanced research projects agency (DARPA) of the U.S. invested USD 2 billion to develop AI technologies such as ML, among others.

Europe is expected to register strong growth in the global market. This is attributed to the rising use of this technology in emerging markets with large populations of skilled workers, such as the United Kingdom and Germany. The regional market is being influenced even further by improved customer access to AI-enabled services and goods. In June 2018, the European Union proposed a Digital Europe Program with a budget of 10.4 billion USD for the period 2021-2027. The program aims at advancing AI technology and deploying its applications across society and the economy. Such active initiatives are likely to create new market opportunities and augment market growth in Europe.

Asia Pacific is expected to exhibit a more robust growth rate over the forecast period. The developing economies in the region such as China, India, and the Philippines pose a vibrant and robust startup ecosystem assisted with an increasingly skilled workforce that drives market growth across the region. Further, In December 2018, Singapore's government created an AI Ethics Advisory Council as a part of its AI Strategy to deploy the applications of AI across different sectors. These are some of the factors that drive market growth in Asia Pacific.

In the Middle East and Africa, the oil-rich Gulf States are making active efforts to diversify their economies through artificial intelligence. For instance, in 2017 Saudi Arabia gave citizenship to a robot. Whereas, the United Arab Emirates announced its first dedicated artificial intelligence minister in October 2018. Also, smart city initiatives, autonomous transport drive the demand for AI capabilities in the region. The Latin American countries such as Brazil, Mexico, and Uruguay are developing new AI policies and coherent strategies to strengthen regional machine learning and advanced technology adoption. The region is expected to pose new lucrative market opportunities in the future.


Microsoft Corporation Introduces New Capabilities in its Product Offerings to Strengthen Market Position

The company offers automated machine intelligence solutions to easily build learning models and accelerate time to market. Microsoft’s Machine Learning Operations (MLOps) or DevOps leverages Azure’s ML capabilities. Responsible ML is the company’s state-of-the-art technology that empowers data scientists to innovate responsibly. To strengthen its market position, Microsoft Corporation tends to introduce new capabilities in its product offerings. For instance, For instance,

  • February 2020 – Oracle Corporation, a leading technology firm launched the Oracle Cloud Data Science Platform. The newly launched platform will be assisting businesses in collaboratively building, training, managing, and deploying machine learning models to improve the performance of data science programs.


  • Amazon Web Services, Inc. (Washington, United States)

  • Baidu, Inc. (Beijing, China)

  • Domino Data Lab, Inc. (California, United States)

  • Microsoft Corporation (Washington, United States)

  • Dataiku (Paris, France)

  • Luminoso Technologies, Inc. (Massachusetts, United States)

  • TrademarkVision (Pennsylvania, United States)

  • SAP SE (Walldorf, Germany)

  • BigML, Inc. (Oregon, United States)

  • Fair Isaac Corporation (FICO) (California, United States)

  • Hewlett Packard Enterprise Development LP (HPE) (California, United States)

  • Intel Corporation (California, United States)

  • IBM Corporation (New York, United States)

  • KNIME.com AG (Zurich, Switzerland)

  • RapidMiner, Inc. (Massachusetts, United States)

  • Angoss Software Corporation (Toronto, Canada)

  • H2O.ai (California, United States)

  • SAS Institute Inc. (North Carolina, United States)

  • Google, Inc. (California, United States)

  • Alpine Data (California, United States)


  • November 2019 - Amazon Web Services Inc. launched EC2 P4d Instance for ML workloads and high-performing computing. Nvidia Corp.'s powerful A100 Tensor Core GPU powers the EC2 P4d instances. Seismic analysis, genomics testing, object identification, and classification are among the advanced cloud applications for which EC2 P4d instances are built.

  • November 2019 - Fair Isaac Corporation announced the release of the Machine-Learning Cyber risk score on the Amazon web services marketplace. AWS marketplace place is a digital catalog of multiple software. Fair Isaac Corporation scoring algorithm leverages micro signal data to quantify the risk of organization cyber-attack risks.


An Infographic Representation of Machine Learning Market

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The market research report provides an in-depth analysis of the market and focuses on key aspects such as leading companies, applications, and adoption of advanced technologies among several industry verticals. Besides this, it offers insights into the machine learning market trends and highlights key industry developments. In addition to the aforementioned factors, the report encompasses several key factors that have contributed to the growth of the advanced market over recent years.

Report Scope and Segmentation



Study Period

  2017 – 2028

Base Year


Forecast Period

  2021 – 2028

Historical Period

  2017 – 2019


  Value (USD Billion)


  Component; Enterprise Size; Deployment; Industry and Region

By Component

  • Solutions

  • Services

By Enterprise Size

  • Small and Medium-sized Enterprises (SMEs)

  • Large Enterprises

By Deployment

  • Cloud

  • On-premise

By Industry

  • Healthcare

  • Retail

  • IT and Telecommunication

  • Banking, Financial Services and Insurance (BFSI)

  • Automotive & Transportation

  • Advertising & Media

  • Manufacturing

  • Others (Energy & Utilities,etc.)

By Region  

  • North America (Component; Enterprise Size; Deployment; End-user and Country)

    • U.S.

    • Canada

  • Europe (Component; Enterprise Size; Deployment; End-user and Country)

    • UK

    • Germany

    • France

    • Scandinavia

    • Rest of Europe

  • Asia Pacific (Component; Enterprise Size; Deployment; End-user and Country)

    • China

    • India

    • Japan

    • Southeast Asia

    • Rest of Asia Pacific

  • The Middle East & Africa (Component; Enterprise Size; Deployment; End-user and Country)

    • GCC

    • South Africa

    • Rest of Middle East & Africa

  • Latin America (Component; Enterprise Size; Deployment; End-user and Country)

    • Brazil

    • Mexico

    • Rest of Latin America

Frequently Asked Questions

According to Fortune Business Insights, the global market size is expected to reach USD 152.24 billion by 2028.

Fortune Business Insights says that the market value stood at USD 11.33 billion in 2020.

By 2028, the market size is expected to reach USD 152.24 billion.

The market is expected to grow at a CAGR of 38.6% in the forecast period (2021-2028).

By component, the solution segment is expected to lead the market during the forecast period.

Substantial investments in AI technology are one of the key drivers for market growth.

Amazon Web Services, Inc., Baidu, Inc., Domino Data Lab, Inc., Microsoft Corporation, Dataiku, Luminoso Technologies, Inc., TrademarkVision, SAP SE, BigML, Inc., Fair Isaac Corporation (FICO), and Hewlett Packard Enterprise Development LP (HPE) are the top companies in the market.

By vertical, the IT and telecommunication segment holds the major market share.

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