Machine Learning Industry 2022 Market Research Report

Report Overview

In 2021, the market for machine learning (ML) was estimated to be worth USD 15.44 billion. From 2022 to 2029, the market is projected to grow at a CAGR of 38.8%, from USD 21.17 billion in 2022 to USD 209.91 billion in 2029.

With data analytics, computers can continuously learn from data, make predictions based on that data, and make changes without being explicitly programmed. This method is known as machine learning, a subfield of artificial intelligence. It would be very challenging to interpret and extract insights from the enormous data volumes generated when people and other environmental variables interact with technology without the speed and sophistication of machine learning and deep learning. ML has considerable potential for developing self-driving cars and “smart cities” with infrastructure that can automatically save time and energy waste and wearable data-driven devices that track fitness and health goals.

Aesthetic Robot in a tech festival

Big data analysis and finding trends and patterns in databases that could otherwise go unnoticed are made easier by machine learning. For instance, ML assists an e-commerce site like Amazon analyze its users’ purchasing patterns and browsing habits, allowing it to present relevant offers, goods, and reminders to users. The outcomes are then applied to serve consumers with relevant adverts.

Machine learning applications in the real world have increased regular activities’ accuracy, efficiency, and usefulness. Machine learning systems are educated precisely to accomplish jobs more quickly and accurately than people, thanks to data science. Many business leaders worldwide use this technology to acquire a competitive edge and link company objectives with employee interests. The market’s anticipated revenue growth will be fueled by growing innovation and development in ML technologies, including No-Code Machine Learning, Tiny Machine Learning, Quantum Machine Learning, Auto Machine Learning, and others. For instance, on May 12, 2022, Allied Digital Services Ltd., a publicly traded provider of global IT solutions, services, and Master Systems integration, presented its new FinTech product, dubbed “FinoAllied.”FinoAllied is an AI-Powered Conversational Banking platform with built-in banking services and transactions ready to be made available to customers through various digital channels banks. Small and midsize banks have several hurdles, such as a need for established digital infrastructure, the ability to develop ground-breaking solutions internally due to resource/project management issues, and the associated high costs. Since FinoAllied only needs to be connected to a bank’s existing IT ecosystem, it takes center stage. The solution serves as a no-code cloud platform, initiating a variety of financial transactions across various voice channels and other digital distribution channels.

Market share of leading machine learning technologies worldwide in 2021

With a market share of 88.71 percent in 2021, Newsle leads the world’s machine learning market, followed by TensorFlow and Torch. The source claims that machine learning software is used to implement artificial intelligence (AI), which enables computers to automatically or “artificially” learn and improve functionality based on experience without being specifically programmed to do so.

Data Graph

COVID-19 pandemic

During the analysis period, COVID-19 is anticipated to favor the machine learning (ML) market growth. This is due to the notable acceleration in the adoption of ML technology across various industries, including healthcare, automotive, and retail. The nation’s health, economic, and social systems have all been significantly impacted by the COVID-19 pandemic.

Regional Analysis

According to regional data, North America’s machine-learning industry held the greatest revenue share in 2021. Along with rising investments in cutting-edge technologies like artificial intelligence, cloud computing, and others, machine learning technology is being employed more and more frequently throughout the region. Demand for advanced technologies is anticipated to increase due to the enormous data that social media and IT companies generate. For instance, Elemeno AI, a cloud-based machine learning company, debuted its Machine Learning Operations (ML-Ops) platform on May 3, 2022, to help organizations use AI’s advantages. It offers data scientists a simple User Experience (UX) for creating machine learning models, starting from scratch.

Due to applications in numerous end-use industries, the Asia-Pacific market is anticipated to see a quicker revenue growth rate during the forecast period. Big Data is used by most businesses in the area to build defenses against cyberattacks. Enterprises are using machine learning technology to identify risks and fraud, which has decreased cybersecurity breaches. The information is subsequently utilized as a component of an advanced analytics solution that provides firms with knowledge regarding cybersecurity issues, including malware/ransomware attacks, hostile insider programs, compromised and vulnerable devices, etc. For instance, on March 17, 2022, the National Association of Software and Service Companies (NASSCOM) published an MLOps playbook through its K-Tech Centre of Excellence for Data Science and AI. It is a compilation of industry-standard frameworks for implementing MLOps. MLOps aims to enhance the caliber of machine learning models, expedite the management procedure, automate deployment, and secure data. Data scientists and operations specialists can use the MLOps suite of methodologies.

The European market is anticipated to see revenue growth throughout the projected period continually. There is an increased need for qualified personnel since the demand for machine learning and AI services is expanding quickly, followed by swift technological improvements. The European Commission claims that legislation and regulations about AI and ML are complex. Although the European AI business is seeing a large increase in market income, the compliance of new systems needs to be improved by the mismatch between legislation and their capabilities. Additionally, European businesses must improve their ability to outsource to nearshore areas.

Market Dynamics

Market Drivers

The development of virtual agents, another important technology, is aiding the development of the machine-learning market’s income. Client inquiries and issues are addressed using chatbots on business websites or email. Businesses like Google and Amazon use virtual agents to offer round-the-clock customer service. Virtual agents employ Artificial Intelligence (AI) technologies to answer customer questions. By establishing and analyzing commonly requested questions, ML is used by AI systems to make it possible for robots to conduct corporate administration responsibilities in the future. The algorithms enable predictive analytics and pattern recognition. Robots can complete repetitive jobs currently carried out by human labor. Growing research and innovation by important firms in creating virtual agents is anticipated to fuel market revenue growth. For instance, on November 4, 2019, Microsoft introduced Power Virtual Agents, a service that facilitates the development of conversational chatbots utilizing a graphical user interface and no programming knowledge. The service aims to democratize bot development and is a part of the Microsoft Power Platform, which also includes Power Apps, Power BI, and Power Automate (formerly known as Microsoft Flow)

Market Restraints

Machine learning mistakes happen frequently. A method may be taught without inclusion if the datasets are small enough. This leads to inaccurate predictions and the display of unrelated advertising to clients. Such mistakes may go unnoticed for a very long period, and fixing them may take considerably longer. Rigid business models also impede the market’s ability to increase its revenue. Since ML is a flexible technology, it needs flexible infrastructure and qualified personnel. However, only some businesses enable innovation and are adaptable in their company practices, restricting market revenue development.

Graph on challenges companies are facing when deploying and using machine learning in 2021

Key Players

  • Microsoft Corporation

  • Apple Inc

  • Google¬†

  • Cisco Systems Inc

  • IBM Corporation

  • Amazon.com Inc

  • Intel Corporation

  • Nuance Communications

  • Wipro Limited

  • Facebook Inc

Questions and Answers

In 2021, the market for machine learning (ML) was estimated to be worth USD 15.44 billion. From 2022 to 2029, the market is projected to grow at a CAGR of 38.8%, from USD 21.17 billion in 2022 to USD 209.91 billion in 2029.

With a market share of 88.71 percent in 2021, Newsle leads the world’s machine learning market, followed by TensorFlow and Torch. The source claims that machine learning software is used to implement artificial intelligence (AI), which enables computers to automatically or “artificially” learn and improve functionality based on experience without being specifically programmed to do so.

The development of virtual agents, another important technology, is aiding the development of the machine-learning market’s income.

Machine learning mistakes happen frequently. A method may be taught without inclusion if the datasets are small enough. This leads to inaccurate predictions and the display of unrelated advertising to clients. Such mistakes may go unnoticed for a very long period, and fixing them may take considerably longer. Rigid business models also impede the market’s ability to increase its revenue. Since ML is a flexible technology, it needs flexible infrastructure and qualified personnel. However, only some businesses enable innovation and are adaptable in their company practices, restricting market revenue development.

  • Microsoft Corporation. (US)

  • Apple Inc (US)

  • Google (US)

  • Cisco Systems Inc. (US)

  • IBM Corporation (US)

  • Amazon.com Inc. (US)

  • Intel Corporation (US)

  • Nuance Communications (US)

  • Wipro Limited (India).

  • Facebook Inc. (US)