Semiconductor and Electronics

Machine Learning Market

Global Industry Analysis and Forecast 2023-2030

Pages : 148

Base Year : 2022

Released Year : November 2023

Format :Pdf Ppt Xls

Report ID:KR172

Author : Priyanka V.

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Base Year

2022

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Forecast Year

2023-2030

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Historical Years

2018-2021

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Market Value (2022)

USD 19.45 billion

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Forecasted Value (2030)

USD 188.34 billion

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CAGR (2023 – 2030)

37.47%

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Fastest Growing Region (2023 - 2030)

Asia-Pacific

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Largest Region

North America

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By Enterprise Type

Small & Medium Sized Enterprises, Large Enterprises

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By Deployment

Cloud, On Premise

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By End User

BFSI, IT & Telecommunication, Healthcare, Retail, Advertising & Media


Market Perspective

The global Machine Learning Market was valued at USD 19.45 billion in 2022 and is projected to reach USD 188.34 billion by 2030, growing at a CAGR of 37.47% from 2023 to 2030.

Global machine learning market is growing rapidly in the forecast period of 2023-2030, due to advancements in technology and increased adoption of artificial intelligence. Additionally, the need for efficient data analysis and prediction tools across various industries, such as healthcare, finance, and retail, further contributes to the market's positive outlook.

Furthermore, increasing availability of big data and the growing awareness of the benefits of machine learning in decision-making increases its demand. Furthermore, the advent of internet of things (IoT) devices and the need for real-time data analysis are also driving the demand for machine learning solutions. As businesses and organizations seek to gain a competitive edge, they are increasingly turning to machine learning algorithms to gain valuable insights from their data and make more informed decisions. As a result, the machine learning market is expected to expand rapidly and revolutionize various industries in the coming years.

Analyst’s Review on Machine Learning Market

Machine learning is transforming various application sectors such as healthcare by aiding in medical diagnostics. For instance, Google’s DeepMind division created an algorithm that can recognize retinal pictures to detect conditions like diabetic retinopathy. Other than this, early detection, reduction in the workload of medical staff, and prompt treatment can be achieved by machine learning technology.

In addition, this technology is used in advertising to forecast consumer behavior and to enhance advertising efforts. There are different types of models that are being used in machine learning, such as AI driven marketing, to augment, automate, and enhance the data into actions. Furthermore, the increased use of machine learning in various applications such as finance and banking in order to complete the loan approval and other asset management tasks, along with its usage in other applications such as publishing, security, and management, is propelling the growth of the market.

Market Definition

Machine Learning Market refers to the market for the development and application of algorithms and statistical models that enable computers to learn and make predictions or decisions without being explicitly programmed. It finds application in various industries such as healthcare, finance, retail, and manufacturing, where machine learning is increasingly being utilized to improve efficiency and accuracy. In addition, with advancements in technology and increasing availability of big data, the machine learning market is expected to grow exponentially in the coming years. This growth is further fueled by the rise of artificial intelligence and the need for automation in various sectors. Healthcare providers, for example, are using machine learning algorithms to analyze patient data and predict diseases, leading to early detection and better treatment outcomes.

Furthermore, machine learning provides various benefits such as flexibility in terms of payment methods, as it offers pay-as-you-use method. The technique uses historical data as inputs in order to predict the new output values. Additionally, the main focus of machine learning is to allow computers to learn automatically without any human assistance. Thus, several methods and techniques are used in the machine learning process, which include reinforcement machine learning algorithms, supervised machine learning algorithms, and others.

Moreover, in finance, machine learning is being used to detect fraud and identify patterns in market data to make informed investment decisions. Similarly, retailers are utilizing machine learning to personalize customer experiences and optimize inventory management. As the demand for intelligent systems continues to rise, the machine learning market is expected to revolutionize industries and shape the future of technology.

Market Dynamics

The machine learning market is experiencing growth due to the increasing amount of data being generated. With the rise in data generation across various industries and companies, there is a growing demand to effectively analyze and extract insights from this data. Machine learning algorithms have the ability to process and analyze large datasets quickly, enabling businesses to make data-driven decisions and gain a competitive advantage.

This has resulted in the widespread adoption of machine learning solutions in sectors like healthcare, finance, retail, and manufacturing, thereby aiding the expansion of the machine learning market. In healthcare, machine learning algorithms are utilized to analyze patient data and identify patterns for early disease diagnosis and treatment. In finance, machine learning is employed for fraud detection and accurate predictions in stock markets.

Furthermore, retail companies leverage machine learning to personalize customer experiences and optimize supply chain management. The manufacturing industry uses machine learning to enhance quality control processes and improve operational efficiency. With the continuous growth of machine learning applications, the machine learning market is expected to further prosper in the upcoming years. However, strict regulatory environments, especially in highly regulated industries like healthcare and finance, can slow down the adoption of machine learning technologies, which may limit the growth of the market.

Segmentation Analysis

The global machine learning market is segmented based on enterprise type, deployment, end user, and geography.

Based on enterprise type, the market is bifurcated into small & medium sized enterprises and large enterprises. Large enterprises have dominated the market, owing to increased use of data science and artificial intelligence into corporate processes. In order to generate high business value, large businesses are focusing on exploiting deep learning, decision optimization, and machine learning. Thus, machine learning is being used widely in large enterprises in order to enhance the required knowledge  from the large data sets, and to reduce the outcome of various challenges.

Based on deployment, the market is bifurcated into cloud and on premise. The cloud segment is expected to hold the largest market share in the year 2022 due to the availability of automated software updates, flexibility updates, and disaster recovery through cloud-based backup systems. Along with this, increased collaboration, monitoring document version control, and data loss prevention with robust cloud storage facilities are factors boosting the adoption of cloud based machine learning software solutions and services.

Geographical Analysis

Based on regional analysis, the global machine learning market is classified into North America, Europe, Asia Pacific, MEA, and Latin America.

North America is expected to dominate the market in coming years due to the presence of leading tech companies in the region. Companies like Google, Microsoft, and Amazon have established themselves as pioneers in the field, attracting top talent and investing heavily in research and development. Additionally, North America has a robust ecosystem of universities and research institutions that are at the forefront of machine learning advancements, providing a constant stream of skilled professionals and innovative ideas. Furthermore, the region's strong infrastructure, access to capital, and supportive government policies have created a favorable environment for the growth of machine learning startups and businesses.

Asia Pacific is expected to be the fastest growing region in the machine learning market owing to developing economies, such as China and the Philippines, have a thriving and dynamic start-up ecosystem, supported by an increasingly trained workforce, along with the increased usage of machine learning in emerging countries with large talent pools, such as India.

Competitive Landscape

The global machine learning industry study will provide valuable insights with an emphasis on the fragmented nature of the global market. Prominent players are focusing on several key business strategies, such as partnerships, mergers & acquisitions, product innovations, and joint ventures to expand their product portfolio and increase their respective market shares across different regions. Expansion & investments involve a range of strategic initiatives including investments in R&D activities, new manufacturing facilities, and supply chain optimization. The major players in the market are:

  • Amazon Web Services, Inc.
  • Baidu Inc.
  • Google Inc.
  • H2O.ai
  • Hewlett Packard Enterprise Development LP
  • Intel Corporation
  • International Business Machines Corporation
  • Microsoft Corporation
  • SAS Institute Inc.
  • SAP SE

Key Developments

  • January 2022 (Collaboration): Stellantis and Amazon collaborated in order to introduce customer-centric connected experiences across millions of vehicles, thereby helping accelerate Stellantis’ software transformation. The agreement will transform in-vehicle experience for Stellantis customers and advance automotive industry’s transition to a software-defined sustainable future.
  • February 2020 (Launch): Oracle Corporation launched “Oracle Cloud Data Science Platform” to help enterprises train, build, manage, and deploy machine learning models to bolster the success of data science projects.

The global Machine Learning Market is segmented as:

By Enterprise Type

  • Small & Medium Sized Enterprises
  • Large Enterprises

By Deployment

  • Cloud
  • On Premise

By End User

  • BFSI
  • IT & Telecommunication
  • Healthcare
  • Retail
  • Advertising & Media

By Region

  • North America
    • U.S.
    • Canada
    • Mexico
  • Europe
    • France
    • UK
    • Spain
    • Germany
    • Italy
    • Russia
    • Rest of Europe
  • Asia Pacific
    • China
    • Japan
    • India
    • South Korea
    • Rest of Asia Pacific
  • Middle East & Africa
    • GCC
    • North Africa
    • South Africa
    • Rest of Middle East & Africa
  • Latin America
    • Brazil
    • Argentina
    • Rest of Latin America
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  • Check Icon Additional Company Profiles
  • Check Icon Additional Countries
  • Check Icon Cross Segment Analysis
  • Check Icon Regional Market Dynamics
  • Check Icon Country-Level Trend Analysis
  • Check Icon Competitive Landscape Customization
  • Check Icon Extended Forecast Years
  • Check Icon Historical Data Up to 5 Years
Frequently Asked Questions (FAQ's)
The global machine learning market is projected to reach USD 188.34 billion by 2030, growing at a CAGR of 37.47% from 2023 to 2030.
The global machine learning Market was valued at 19.45USD billion in 2022.
The major driving factor for the market growth is increasing machine learning applications healthcare sector, along with the integration of machine intelligence with the analytics solutions boosts the market growth.
Top manufacturers of machine learning market are Amazon Web Services, Inc., Baidu Inc., Google Inc., H2o.AI, Hewlett Packard Enterprise Development LP, Intel Corporation, International Business Machines Corporation, Microsoft Corporation, SAS Institute Inc., and SAP SE, among others.
Europe is the fastest growing region in the forecasted period (2023-2030).
By enterprise type, large enterprises will hold the maximum share in the machine learning market in the forecast period.
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