Machine Learning (ML) Market Size, Share & COVID-19 Impact Analysis, By Enterprise Type (Small & Mid-sized Enterprises (SMEs) and Large Enterprises), By Deployment (Cloud and On-premise), By End-Use Industry (Healthcare, Retail, IT and Telecommunication, BFSI, Automotive and Transportation, Advertising and Media, Manufacturing, and Others), and Regional Forecast, 2023-2030

The global Machine Learning (ML) market size was valued at USD 19.20 billion in 2022. The market is expected to grow from USD 26.03 billion in 2023 to USD 225.91 billion by 2030, exhibiting a CAGR of 36.2% during the forecast period.

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 humans learn. Increasing adoption of AI and ML technologies in various end-use industries, such as healthcare, automotive, retail, and manufacturing, among others, will play an important role in the market growth. Furthermore, in 2020, several countries adopted quarantine measures and social distancing policies to mitigate the impact of the COVID-19 pandemic. Developers and researchers intended to use ML tools to analyze the effects of these measures and policies. For instance,

• In April 2020, Massachusetts Institute of Technology (MIT) researchers developed a model that uses 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 initiatives are likely to surge the demand for advanced ML capabilities.

COVID-19 IMPACT

COVID-19 Pandemic Created Unprecedented Market Opportunities for Leading Companies

The COVID-19 outbreak had rapidly accelerated the Machine Learning market growth, and this trend is expected to continue during the assessment period as well. This is due to the rising adoption of ML technology in automotive, retail, healthcare, and other sectors.

The application of AI technology helped researchers combat the COVID-19 pandemic. For instance, according to the Brookings Institution, researchers in South Korea used geolocation data and surveillance camera footage to track coronavirus patients. The data scientists used this footage and machine intelligence algorithms to predict the location of the next outbreak and inform the responsible authorities and track COVID-19-positive patients in real-time. Such active initiatives may surge the demand for machine learning solutions over the coming years.

LATEST TRENDS

Integration of Machine Intelligence with Analytics Solutions to Boost Market Progress

In recent years, the field of retail analytics has expanded rapidly. Many e-commerce businesses, such as Alibaba, eBay, and Amazon, have increased their sales and improved consumer satisfaction by using advanced data analytics technologies. Cognitive speech coding approaches based on ML principles have emerged as a result of research & development in speech and voice recognition technologies.

Machine learning is likely to become an important trend in security analytics as firms embrace advanced security frameworks. As large volumes of data are created and exchanged over numerous networks, cyber professionals find it quite difficult in analyzing and tracking potential cyber threats. As these threats are becoming more widespread and complex, machine learning algorithms are assisting security teams and organizations in predicting, tracking, and recognizing cyber-attacks more quickly. These factors will expand the market size.

DRIVING FACTORS

Increasing Applications in the Healthcare Sector Likely to Boost Market Growth

ML technology is already being used in a variety of healthcare applications. In this industry vertical, this technology assesses millions of distinct data points and predicts outcomes as well as provides quick risk scores and exact resource allocation.

One of the most important applications of this technology in healthcare is diagnosing and detecting conditions/illnesses that are sometimes difficult to identify. This can include various hereditary diseases and cancers that are difficult to detect in their early stages. A prominent example of this is the IBM Watson Genomics, which shows how genome-based tumor sequencing, combined with cognitive computing, might aid in cancer diagnosis. Berg, a biopharmaceutical giant, utilizes AI to produce therapeutic solutions for areas such as cancer.

Computer vision is a revolutionary technique that combines ML and deep learning. It has been accepted by Microsoft's InnerEye program, which focuses on image diagnostic tools for image analysis. These factors are likely to boost the market growth.

RESTRAINING FACTORS

Technical Limitations and Lack of Accuracy to Impede Market Progress

ML platform offers several benefits that can drive the market growth. However, this technology lacks certain parameters that can hinder market growth. One of the major restraining factors of ML platform is inaccurate and undeveloped algorithms. Precision is very important in Big Data and machine learning, and inaccurate algorithms can result in the production of defective items. Therefore, human interaction is required to put all the parameters of the system in place and ensure that the error margin is close or equal to zero. This factor may hamper the market prospects.

SEGMENTATION

By Enterprise Type Analysis

Large Enterprises to Increase their Tech Spending to Deploy AI and ML Technologies

Based on enterprise type, the market is divided into small & mid-sized enterprises and large enterprises. Large enterprises segment accounted for the largest market share in 2022. The implementation of data science and AI technology is growing across these organizations to introduce quantitative insights into their operations. Large enterprises are also working on harnessing deep learning, artificial learning, and optimization of decisions to provide high-quality services.

Small and mid-sized enterprises segment is likely to exhibit a significant growth rate during the forecast period. ML and AI are projected to become the key technologies enabling SMEs to access digital resources while reducing their ICT investments.

By Deployment Analysis

Increasing Demand for Cloud-based Solutions to Aid Adoption of ML Solutions

In terms of deployment, the market is classified into cloud and on-premise. The cloud segment is expected to record 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 increased 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 is attributed to the large calculation capacity and data security compliance offered by this deployment model.

By End-use Industry Analysis

Rising Machine Intelligence Applications in the Healthcare Industry to Witness Remarkable Market Growth

Industries are working with large amounts of data leverage ML technology to derive real-time insights. These insights enable end-users to gain more advantage over competitors and work more efficiently.

During the pre-COVID-19 scenario, the use of wearable devices and sensors to assess patients’ health in real-time surged the demand for machine intelligence applications in the healthcare industry. The technology helps medical experts identify trends and analyze data to improve diagnosis and treatment, thereby increasing the Machine Learning market share.

REGIONAL ANALYSIS

The global market is studied across Europe, Asia Pacific, the Middle East & Africa, and Latin America by geography.

North America captured the maximum market share in 2022. The presence of prominent R&D investors, such as Oracle Corporation, Amazon.com, and IBM Corporation, has expanded the regional market size. Moreover, availability of established IT infrastructure and huge investments are expected to drive the market growth in North America. For instance, the Defense Advanced Research Projects Agency (DARPA) of the U.S. invested around USD 2 billion to deploy machine learning and other 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 that have a large population of skilled workers such as the U.K. and Germany. The regional market is being further influenced by improved customer access to AI-enabled services and goods. The rapid digitization triggered by the COVID-19 pandemic has made companies invest significantly in IT technologies. According to a recent McKinsey survey, IT spending has grown by 25% in Europe across all industries, compared to 2020, with most of the digital technology leaders increasing their investments. These developments will create new market opportunities and augment the market growth in Europe.

Asia Pacific is anticipated to record a more robust growth rate during the forecast period. The region’s developing economies, such as China, India, and the Philippines, have a vibrant and robust startup ecosystem that is assisted by a skilled workforce, which will bolster the regional market growth. The Japanese government is also taking various initiatives to encourage the use of artificial intelligence across the country and enhance the adoption of machine learning services, which will play an important role in improving the market forecast in Japan. These are some of the key factors that will spur the APAC market growth.

In the Middle East & Africa, the oil-rich Gulf states are taking active efforts to diversify their economies through artificial intelligence. Most Gulf countries have recognized the prominence of advanced technology and are focusing on the development of novel technologies. The UAE leads the Arab world in innovation and adoption of technologies. Also, smart city initiatives and autonomous transport will boost the demand for AI in the region.

Latin American countries, such as Brazil, Mexico, and Uruguay, are developing new AI policies and coherent strategies to strengthen the adoption of advanced technologies. This region is expected to create new and lucrative market opportunities in the future.

KEY INDUSTRY PLAYERS

Key Players to Introduce New Functionalities in their Existing Offerings to Strengthen Market Position

The companies operating in the global market offer automated machine intelligence solutions to easily build learning models and accelerate time to market. Microsoft’s Machine Learning Operations (MLOps) or DevOps utilizes Azure’s ML capabilities that empower data scientists to innovate critical processes responsibly. Microsoft Corporation is consistently introducing new capabilities in product offerings to strengthen its market position.

List of Key Companies Profiled:

• IBM Corporation (U.S.)


• SAP SE (Germany)


• Oracle Corporation (U.S.)


• Hewlett Packard Enterprise Company (U.S.)


• Microsoft Corporation (U.S.)


• Amazon, Inc. (U.S.)


• Intel Corporation (U.S.)


• Databricks (U.S.)


• SAS Institute Inc. (U.S.)


• BigML, Inc. (U.S.)

KEY INDUSTRY DEVELOPMENTS

• January 2022– Acquia introduced advanced retail ML models for its customer data platform to increase customer lifetime value. With this launch, the company aimed to help retailers gain a holistic view of their business. Acquia assists retailers in understanding levers within their marketing and sales efforts.


• April 2021: Microsoft Corporation launched an open database for health & genomics, transportation, labor & economics, population & safety, and other areas to increase the accuracy of machine learning models that use publicly available datasets. Moreover, this enables the firm to provide Hyperscale insights by utilizing Azure Open Datasets in conjunction with Azure's data analytics and ML solutions, boosting ML-as-a-services (MLaaS) sales.


• May 2021: Google Cloud introduced Vertex AI, a managed ML solution/platform which enables organizations to accelerate the maintenance and deployment of AI models. In addition, Vertex AI uses Google Cloud services for creating ML under one API and UI to streamline the process of deploying, training, and building ML models at scale.


• February 2020: Oracle Corporation introduced the Oracle Cloud Data Science Platform. The platform was designed to assist businesses in collaboratively training, building, deploying, and managing ML models to enhance the performance of data science programs.


• May 2020– Azure machine learning is a cloud-based service that allows users to create and manage ML solutions. It assists data scientists and engineers in maximizing the use of their existing model creation and data processing abilities and frameworks. It also helps them in distributing, scaling, and deploying their workloads on cloud.

REPORT COVERAGE

The global 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 market trends. In addition to the above-mentioned factors, the report includes other aspects that have contributed to the growth of the market in recent years.

REPORT SCOPE & SEGMENTATION