The global machine learning (ML) market size was valued at USD 15.44 billion in 2021. The market is expected to grow from USD 21.17 billion in 2022 to USD 209.91 billion by 2029, exhibiting a CAGR of 38.8% during the forecast period. The global impact of COVID-19 pandemic has been unprecedented and staggering, with the machine learning technology witnessing higher-than-anticipated demand across all regions compared to pre-pandemic levels. Based on our analysis, the global market exhibited a higher growth of 36.1% in 2020 compared to 2019.
Machine learning is a subset of artificial intelligence (AI). It is a data analytics method that teaches computers to learn from algorithms and data and quickly imitate the way that humans learn. Increasing adoption of artificial intelligence (AI) and ML technology in various end-use industries such as healthcare, automotive, retail, and manufacturing, among others plays an important role in market growth. Furthermore, in 2020, 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.
The field of artificial 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. Besides, many companies are strengthening their deep learning capabilities to drive innovation which is expected to drive machine learning market growth across industries and regions.
COVID-19 Pandemic to Create Unprecedented Market Opportunities for Leading Companies
The COVID-19 is expected to positively impact the growth of this market during the analysis period. This is attributed to the significant acceleration in the adoption of this technology in healthcare, automotive, and retail, among others. The COVID-19 pandemic has significantly affected country’s health, financial, and social systems.
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 instance, according to The Brookings Institution, in South Korea, researchers use surveillance camera footage and geolocation data to track coronavirus patients. The data scientists use this surveillance camera footage data and with the help of machine intelligence algorithms they predict the location of the next outbreak and inform the responsible authorities, to track the COVID positive patients in real-time. Such active initiatives are likely to surge the demand for machine intelligence solutions in the upcoming period. Moreover, the companies that have invested and deployed disruptive technologies such as edge computing, Artificial Intelligence (AI), connected devices, and ML during the COVID-19 pandemic started realizing that these technologies are helping the business to recover the initial impacts of COVID-19 and drive business automation in future.
Hence, considering all the above factors, artificial intelligence (AI), cloud computing, and other technologies are expected to be the disruptive technologies to enable future platforms.
Integration of Machine Intelligence with Analytics-driven Solutions to be a Growing Market Trend
In recent years, the field of retail analytics has exploded. Many e-commerce businesses, like Amazon, Alibaba, and eBay, use advanced data analytics technologies to increase sales and improve consumer satisfaction. Cognitive speech coding approaches based on ML principles have emerged as a result of research and development in speech and voice recognition technologies.
As firms embrace more advanced security frameworks, machine learning will become an important trend in security analytics. With such a large amount of data being created and exchanged over numerous networks, cyber professionals have a huge difficulty in tracking and analyzing potential cyber threats and assaults. Machine learning algorithms also assist organizations and security teams in anticipating, tracking, and recognizing cyber-attacks more quickly as cyber threats become more widespread and complex. As a result, incorporating advanced learning capabilities into analytics-driven solutions is certainly becoming a major industry trend.
Increasing Applications in Healthcare is likely to Boost the Market Growth
ML technology is already assisting in a variety of circumstances in healthcare. In healthcare, this technology helps to assess millions of distinct data points and predict outcomes, as well as give fast risk scores and exact resource allocation, among many other uses.
Identifying Diseases and Diagnosis: One of the most important application of this technology in healthcare is detecting and diagnosing illnesses and conditions that are sometimes difficult to identify. This can include anything from cancers that are difficult to identify in their early stages to other hereditary diseases. IBM Watson Genomics is a prominent illustration of how combining cognitive computing with genome-based tumor sequencing might aid in the diagnosis of cancer. Berg, a biopharmaceutical giant, utilizes AI to produce therapeutic solutions in areas such as cancer.
Medical Imaging Diagnosis: The revolutionary technique known as Computer Vision combines ML and deep learning. This has been accepted by Microsoft's InnerEye programme, which focuses on image diagnostic tools for image analysis.
These factors are likely to boost market growth.
Technical Limitations and Lack of Accuracy to Impede the Market Growth
The ML platform offers a vast number of benefits that help in driving the market growth. However, the platform lacks certain parameters that are expected to hinder market growth. One of the major restraining factors of the market is the presence of inaccuracy in this algorithms, which are occasionally undeveloped. Precision is very important in big data and machine learning manufacturing businesses. A little inaccuracy in the algorithm might result in the production of incorrect items. As a result, human interaction is required until the system has all of the parameters in place and the error margin is close to or equal to zero. Thus, this factor may hinder market growth.
By Component Analysis
Machine Learning Solutions to Account for the Majority Market Share
By component, the global market is segmented into solutions and services. The solution has captured maximum market share in 2021 and is expected to maintain its dominance in the forthcoming era. The solutions provided by the key market players include IBM Corporation’s Watson, Oracle ML, Microsoft Corporation’s Azure, 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. The services are anticipated to witness significant growth during the forecast period. These services help industries make informed decisions actionable strategies enhancing operation workflow, end-to-end risk, and compliance management capabilities.
By Enterprise Size Analysis
Small and Mid-Sized Enterprises to Increase their Tech Spending 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 accounted for the largest machine learning market share in 2021. This is attributed to the growing implementation of artificial intelligence, and data science technology 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.
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 enabling SMEs to reduce ICT investments and access digital resources.
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. Whereas, 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 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 End-user Analysis
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-19 scenario, the advent of wearable devices and sensors 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 augmented 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 aspects that drive the demand for this technology in the financial and retail industries.
Automotive and transportation are projected to witness significant growth in the coming years. Research & development in self-driving cars autonomous transportation drives the demand for advanced solutions.
The global market scope is classified across five regions, namely North America, Europe, Asia Pacific, 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.
Europe is expected to register strong growth in the global market. This is attributed to the rising use of ML technology in emerging markets with large population of skilled workers, such as the U.K. and Germany. The regional market is being influenced 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, the Japanese government is taking various initiatives to encourage artificial intelligence across the country, along with the surge in adoption of machine learning services which plays an important role in driving the market in Japan. 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. Most Gulf countries have recognized the prominence of advanced technology and continually focus on the development of novel technologies. UAE leads the Arab world in innovation and adoption of technologies. Also, smart city initiatives autonomous transport drives the demand for AI capabilities in the region. Latin American countries such as Brazil, Mexico, and Uruguay are developing new AI policies and coherent strategies to strengthen regional advanced technology adoption. The region is expected to pose new lucrative market opportunities in the future.
KEY INDUSTRY PLAYERS
Market Leaders to Introduces New Capabilities in their 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 MLOps or DevOps leverages Azure’s ML capabilities. Microsoft Corporation tends to introduce new capabilities in product offerings to strengthen its market position. The company’s state-of-the-art technology “Responsible” empowers data scientists to innovate responsibly. For instance,
April 2021: Microsoft Corporation has launched an open database for transportation, health and genomics, population and safety, labor and economics, and others to increase the accuracy of ML models using publicly available datasets. This also enables the firm to provide Hyperscale insights utilizing Azure Open Datasets in conjunction with Azure's ML and data analytics solutions, boosting MLaaS sales.
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 ML models to improve the performance of data science programs.
List of the Key Companies Profiled:
- IBM Corporation (New York, U.S.)
- SAP SE (Walldorf, Germany)
- Oracle Corporation (Texas, U.S.)
- Hewlett Packard Enterprise Company (Texas, U.S.)
- Microsoft Corporation (Washington, U.S.)
- Amazon, Inc. (Washington, U.S.)
- Intel Corporation (California, U.S.)
- Fair Isaac Corporation (California, U.S.)
- SAS Institute Inc. (North Carolina, U.S.)
- BigML, Inc. (Oregon, U.S.)
KEY INDUSTRY DEVELOPMENTS
- January 2022– Acquia introduced advanced retail machine learning models for its customer data platform to increase customer lifetime value. With this launch, the company aims to help retailers gain a holistic view of their business. It assists retailers in understanding levers within their marketing and sales efforts.
- May 2020– Azure is a cloud-based service that allows users to create and manage ML solutions. It's intended to assist data scientists and engineers in maximizing the use of their existing data processing and model creation abilities and frameworks. Assist them in distributing, scaling and deploying their workloads to the cloud as well.
The market research report provides a comprehensive analysis of the market. It focuses on key aspects such as prominent companies, and leading applications of the product. Besides this, the report highlights key industry developments and offers insights into the machine learning market trends. In addition to the above-mentioned factors, the report includes several factors that have contributed to the growth of the market over recent years.
REPORT SCOPE & SEGMENTATION
Value (USD billion)
Component, Enterprise Size, Deployment, End-user, Region
By Enterprise Size
Frequently Asked Questions
How much was the global machine learning (ML) market worth in 2021?
Fortune Business Insights says that the market was valued at USD 15.44 billion in 2021.
How much will the market be worth in 2029?
Fortune Business Insights says that the market is expected to reach USD 209.91 billion in 2029.
What compound annual growth rate (CAGR) will the global market grow?
Growth of 38.8% CAGR will be observed in the market during the forecast period (2022-2029)
Which End-user segment is expected to lead the market during the forecast period?
The IT and Telecommunication sector is expected to lead during the forecast period within the End-user segment.
What are the key market drivers?
Increasing machine learning applications in the healthcare industry are likely to drive the market.
Who are the top companies in the market?
Amazon Web Services, Inc., Microsoft Corporation, IBM Corporation, Intel Corporation, Oracle Corporation, SAP SE, Fair Isaac Corporation (FICO), and Hewlett Packard Enterprise Development LP (HPE) are the top companies in the global market.
Which segment is expected to grow significantly during the forecast period?
The healthcare industry is expected to grow exponentially at the highest CAGR.
What is the revenue of the North American market in 2021?
The revenue of the market in North America in 2021 was USD 5.56 billion.