The Global Machine Learning Market size is expected to reach $408.4 billion by 2030, rising at a market growth of 36.7% CAGR during the forecast period.
The usage of machine learning has grown widely by retailers to improve customer experiences. Consequently, Retail segment acquired $3,839.1 million revenue in the market in 2022. In order to process large datasets, identify pertinent metrics, recurrent patterns, anomalies, or cause-and-effect relationships among variables, and thus gain a deeper understanding of the dynamics guiding this industry and the contexts where retailers operate, machine learning is used in the retail industry. Machine learning's expansion in the retail sector is fueled by its capacity to improve consumer experiences, streamline processes, and boost revenue.
The major strategies followed by the market participants are Partnerships as the key developmental strategy to keep pace with the changing demands of end users. For instance, In March, 2023, AWS came into collaboration with NVIDIA to jointly build on-demand AI infrastructure intended for training sophisticated large language models (LLMs) and developing generative AI applications. In June, 2023, Microsoft partnered with HCLTech to help businesses leverage generative artificial intelligence and develop joint solutions to allow businesses to achieve better outcomes and improve business transformation.
Based on the Analysis presented in the KBV Cardinal matrix; Google LLC (Alphabet Inc.) and Microsoft Corporation are the forerunners in the Market. In March, 2022, Google entered into a partnership with BT to offer excellent customer experiences, decrease costs, and risks, and create more revenue streams and to enable BT to get access to hundreds of new business use cases to solidify its goals around digital offerings and developing hyper-personalized customer engagement. Companies such as IBM Corporation, Hewlett-Packard enterprise Company and Intel Corporation are some of the key innovators in the Market.
There is a rising need for intelligent business processes as organizations depend increasingly on data to inform decisions and boost operational effectiveness. These procedures use machine learning algorithms to automate decision-making and streamline corporate operations, which boosts productivity and profits. By utilizing AutoML, companies can increase performance, lower costs, and streamline processes, giving them a competitive advantage. In addition, AI-powered automation has been demonstrated to increase productivity significantly. By automating the creation and deployment of machine learning models, the automated market can assist firms in achieving these outcomes.
Businesses may save the expenses of investing in costly infrastructure and employing specialist people by adopting AutoML solutions. Additionally, by boosting operational effectiveness and enhancing decision-making, AI solutions' quicker development and implementation may lead to cost savings. There will probably be a proliferation of new use cases and applications as more organizations employ AutoML technologies, boosting innovation and market growth. Additionally, the democratization of machine learning may help companies extend their offers and tap into new markets, increasing sales and market share.
Large volumes of data, sometimes including sensitive and private data, are necessary for machine learning. Individuals and organizations may hesitate to provide their data for ML purposes because of privacy and security concerns. Various legal and regulatory frameworks, including industry-specific rules, consumer protection laws, and anti-discrimination laws, must be complied with while using machine learning (ML). Failure to comply with these criteria may result in legal responsibilities, financial fines, harm to one's image, and a decline in public confidence. Organizations may be unsure and wary because of the possible legal issues of ML deployment. These factors are anticipated to impede market expansion in the ensuing years.
The leading players in the market are competing with diverse innovative offerings to remain competitive in the market. The above illustration shows the percentage of revenue shared by some of the leading companies in the market. The leading players of the market are adopting various strategies in order to cater demand coming from the different industries. The key developmental strategies in the market are Partnerships & Collaborations.
On the basis of enterprise size, the market is segmented into SMEs and large enterprises. In 2022, the large enterprises segment witnessed the largest revenue share in the market. Large enterprises are increasingly using cloud-based machine learning platforms and services. Machine learning model training and deployment are made feasible by cloud platforms' scalable and affordable architecture. Due to the services like Google Cloud AI Platform, Amazon Web Services (AWS), and Microsoft Azure Machine Learning, which provide pre-built models, distributed training capabilities, and infrastructure management, Machine learning does not need big infrastructure expenditures for large businesses.
By end-user, the market is categorized into healthcare, BFSI, retail, advertising & media, automotive & transportation, agricultural, manufacturing, and others. In 2022, the advertising & media segment dominated the market with the maximum revenue share. One of the major trends is hyper-personalization, in which machine learning algorithms examine vast amounts of user data to create highly relevant and individualized advertisements that increase engagement and conversion rates. A considerable focus is now being placed on employing machine learning to identify ad fraud.
Based on components, the market is divided into services, software, and hardware. The hardware segment acquired a substantial revenue share in the market in 2022. It could be connected to the growing popularity of gear designed for machine learning. The development of specialized silicon processors with AI and ML capabilities is fueling hardware adoption. As more powerful processing devices are created by companies like SambaNova Systems, the market is predicted to keep expanding.
| Report Attribute | Details |
|---|---|
| Market size value in 2022 | USD 34.6 Billion |
| Market size forecast in 2030 | USD 408.4 Billion |
| Base Year | 2022 |
| Historical Period | 2019 to 2021 |
| Forecast Period | 2023 to 2030 |
| Revenue Growth Rate | CAGR of 36.7% from 2023 to 2030 |
| Number of Pages | 280 |
| Number of Table | 393 |
| Report coverage | Market Trends, Revenue Estimation and Forecast, Segmentation Analysis, Regional and Country Breakdown, Competitive Landscape, Market Share Analysis, Companies Strategic Developments, Company Profiling |
| Segments covered | Component, Enterprise Size, End-use, Region |
| Country scope | US, Canada, Mexico, Germany, UK, France, Russia, Spain, Italy, China, Japan, India, South Korea, Singapore, Malaysia, Brazil, Argentina, UAE, Saudi Arabia, South Africa, Nigeria |
| Growth Drivers |
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| Restraints |
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Region wise, the market is analyzed across North America, Europe, Asia Pacific, and LAMEA. In 2022, the North America region led the market with the maximum revenue share. In North America, there is a rising focus on moral AI and responsible AI practices due to machine learning's expanding social influence. Fairness, accountability, and openness are prioritized by organizations while developing machine learning models and algorithms. Biases are being lessened, privacy is protected, and ethical issues about AI applications are being addressed. Legislative frameworks, rules, and standards are being created to oversee the proper use of machine learning in the area.
Free Valuable Insights: Global Machine Learning Market size to reach USD 408.4 Billion by 2030
The market research report covers the analysis of key stake holders of the market. Key companies profiled in the report include Amazon Web Services, Inc. (Amazon.com, Inc.), Baidu, Inc., Google LLC (Alphabet Inc.), H2O.ai, Inc., Hewlett-Packard enterprise Company (HP Development Company L.P.), Intel Corporation, IBM Corporation, Microsoft Corporation, SAS Institute, Inc., SAP SE.
By Enterprise Size
By Component
By End-use
By Geography
The Market size is projected to reach USD 408.4 billion by 2030.
Enabling Fast Decision-Making and Saving Costs are driving the Market in coming years, however, Legal and Ethical Issues restraints the growth of the Market.
Amazon Web Services, Inc. (Amazon.com, Inc.), Baidu, Inc., Google LLC (Alphabet Inc.), H2O.ai, Inc., Hewlett-Packard enterprise Company (HP Development Company L.P.), Intel Corporation, IBM Corporation, Microsoft Corporation, SAS Institute, Inc., SAP SE.
The Services segment is leading the Market by Component in 2022; thereby, achieving a market value of $212.3 billion by 2030.
The North America region dominated the Market by Region in 2022, and would continue to be a dominant market till 2030; thereby, achieving a market value of $141.9 billion by 2030.
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