What Is The Size Of Global Machine Learning Industry?
Global Machine Learning market is growing at a CAGR of ~% in 2017-2022 and is expected to reach ~USD Bn by 2028F.
The Machine Learning Market is largely driven by increase in demand for cloud-based solutions, artificial intelligence, and the cognitive computing market
The Machine Learning as a Service (MLaaS) Market is expected to grow as demand for a cloud-based solution increases, including growing demand for cloud computing, rise in adoption of analytical solutions, growth of artificial intelligence & cognitive computing market, increased application areas, and lack of trained professionals.
In addition, several organizations are unwilling to adopt ML technologies due to concerns regarding data security. For many regulated industry sectors such as banking, insurance, healthcare, and government, data security is crucial and any failure in data security may result in major problems.
Furthermore, COVID-19 caused an acceleration in the migration of public cloud solutions and some of the applications of AI to help in tracing patients during the pandemic. Since cloud service elasticity could meet the unexpected rise in demand, the need for AI services had seen growth, and many cloud providers offered Machine Learning as a Service (MLaaS). Several countries used population surveillance methods to track and trace COVID-19 cases.
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Global Machine Learning Market by components
The Global Machine Learning market is segmented by Components into Software Tools and Services.
The service segment dominated the Machine Learning as a Service (MLaaS) Market in 2022 and is expected to maintain its dominance during the forecast period.
The market for ML services is expected to grow due to increasing cloud applications and the growth of end-use industries in developing economies. To enhance the usage of ML services, industry participants focus on implementing technologically advanced solutions, for instance, the use of ML services in the healthcare sector for cancer detection, as well as checking ECG and MRI. ML services features, such as cost reduction, demand forecasting, real-time data analysis, and increased cloud use, are projected to open considerable prospects for the market.
Global Machine Learning Market By Application
The Global Machine Learning Market is segmented by Application into Marketing & Advertising, Predictive Analytics, Automated Network Management, Fraud detection and risk Analytics, Network Analytics and Automated Traffic Management and Others.
Network analytics and automated traffic management segment accounted for the majority share of the Global Machine Learning as a Service (MLaaS) Market in 2021 and is expected to showcase the highest growth rate during the forecast period (2022-2028).
In 2021, Amazon released SageMaker Studio, the first ML IDE. This application provides a web-based interface through which clients can run all ML model training tests in a single environment.
Global Machine Learning Market By End-User
The Global Machine Learning market is segmented by End-User into Banking, Financial, Services, and Insurance, IT and Telecom, Automotive, Healthcare, Aerospace and Defense, Retail, Government and Others.
The healthcare segment holds the largest market share in Global Machine Learning as a Service (MLaaS) Market in 2022.
Growing adoption of ML solutions by various retail and healthcare service providers is expected to boost the Machine Learning as a Service market during the forecast period. Major market prospects are anticipated to be unlocked by the advantages provided by ML services, such as demand forecasting, cost reduction, real-time data analysis, and a rise in the use of the cloud market.
Global Machine Learning Market By Enterprise
The Global Machine Learning market is segmented by Enterprise into SMEs and Large enterprises.
SME segment is estimated to capture the largest market share of the Global Machine Learning as a Service (MLaaS) Market in 2022 and is expected to showcase the highest growth rate during the forecast period (2022-2028).
ML lets SMEs optimize their processes on a low budget in comparison with starting things from scratch. For SMEs the ‘pay for what you use or ‘pay as you grow system offered by most MLaaS providers makes it both budget-friendly and time-effective to integrate ML into their businesses while not requiring a team with specific technical capabilities. With the help of predictive analytics, machine learning algorithms not only provide real-time data but also predict future instances.
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Key Topics Covered in the Report
- Snapshot of the Global Machine Learning as a Service (MLaaS) Market
- Industry Value Chain and Ecosystem Analysis
- Market size and Segmentation of the Global Machine Learning as a Service (MLaaS) Market
- Historic Growth of the Overall Global Machine Learning as a Service (MLaaS) Market and Segments
- Competition Scenario of the Market and Key Developments of Competitors
- Porter’s 5 Forces Analysis of Global Machine Learning as a Service (MLaaS) Industry
- Overview, Product Offerings, and SWOT Analysis of Key Competitors
- COVID-19 Impact on the Overall Global Machine Learning as a Service (MLaaS) Market
- Future Market Forecast and Growth Rates of the Total Global Machine Learning as a Service (MLaaS) Market and by Segments
- Market Size of Application/End User Segments with Historical CAGR and Future Forecasts
- Analysis of the Machine Learning as a Service (MLaaS) Market
- Major Production / Consumption Hubs in the Major within Each Region
- Major Production/Supply and Consumption/Demand Hubs within Each Major Country
- Major Country-wise Historic and Future Market Growth Rates of the Total Market and Segments
- Overview of Notable Emerging Competitor Companies within Each Region
Notable Emerging Companies Mentioned in the Report
- Reverie
- Anodot
- Arturo
- ml
- Eightfold AI’s
Key Target Audience – Organizations and Entities Who Can Benefit by Subscribing This Report
- Machine Learning as a Service (MLaaS) Solution Companies
- Potential Investors in Machine Learning as a Service (MLaaS) Companies
- IoT Solutions Providers
- Government Investors
- AI Solution Providers
- Networking Companies
- Cloud Developers
- Research & Development Institutes
- Venture Capitalists
- Healthcare IoT Companies
- Telecommunication Service Providers
- Software Developers
- Electronic/Smart Device Manufacturers
- Finance and Banking Institutes
- Marketing Companies
Time Period Captured in the Report
- Historical Period: 2017-2021
- Forecast Period: 2022E-2028F
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