Machine Learning Market to Surpass USD 240.84 Billion by 2033, exhibiting a CAGR of 36.7%

The machine learning market size has grown exponentially in recent years. It will grow from $50.2 billion in 2023 to $68.88 billion in 2024 at a compound annual growth rate (CAGR) of 37.2%. The growth in the historic period can be attributed to advancements in algorithms, increasing data availability, computing power enhancement, industry adoption and integration, iot and edge computing integration.

The machine learning market size is expected to see exponential growth in the next few years. It will grow to $240.84 billion in 2028 at a compound annual growth rate (CAGR) of 36.7%. The growth in the forecast period can be attributed to explainability and ethical ai concerns, exponential data growth, expansion of edge computing, growing integration of ai and ml, global demand for predictive analytics. Major trends in the forecast period include continued algorithmic innovations, rise of big data technology, automated machine learning (automl), federated learning, integration of ml with other technologies, industry-specific ml solutions.

Market Overview -
Machine learning as a service refers to the delivery of machine learning capabilities and tools as cloud-based services. It allows individuals and organizations to access and use machine learning algorithms, models, and infrastructure without the need for significant investment in hardware, software, or expertise in machine learning.

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Accelerating Demand For Artificial Intelligence Fuels Machine Learning As A Service Market Growth
The increasing demand for artificial intelligence (AI) is expected to propel the growth of machine learning as a service market going forward. Artificial intelligence (AI) is the development of computer systems that can do activities that normally require human intelligence. AI plays an important role in machine learning as a service (MLaaS) by enabling automated model training, prediction, and continuous optimization, enhancing the accessibility and efficiency of machine learning for diverse applications. For instance, in May 2022, according to the IBM Global AI Adoption Index 2022 by IBM, a US-based technology corporation, a poll conducted of 7,502 businesses found that, 35-36% of global companies were already implementing AI, and 42-64% were exploring its potential. 64% of businesses believe that AI will improve business productivity, and 42% believe it will streamline job processes. AI adoption is growing steadily, up 4% from 2021. Therefore, the increasing demand for artificial intelligence is driving the growth of the machine learning as a service market.

Competitive Landscape -
Major companies operating in the machine learning as a service market report are Google LLC, Microsoft Corporation, Amazon Web Services Inc., International Business Machines Corporation (IBM), Oracle Corporation, Rockwell Automation, SAS Institute Inc., Fair Isaac Corporation (FICO), Hewlett Packard Enterprise, Databricks Inc., TIBCO Software Inc., Cloudera Inc., Dataiku, Domino Data Lab, CognitiveScale, Sift Science Inc., Iflowsoft Solutions Inc., Seldon Technologies Limited, BigML Inc., Monkeylearn Inc., Neural Designer, Datatron, H2O.ai Inc., Verta AI, Yottamine Analytics, Explorium, Paperspace

Focus On Innovative Solutions To Drive Efficiency
Major companies operating in the machine learning as a service market are developing innovative products, such as the Watsonx platform, to gain a competitive edge in the market. Watson is a cognitive computing platform that uses artificial intelligence and machine learning to analyze large volumes of data and provide insights, predictions, and natural language interaction capabilities for a variety of applications. In July 2023, International Business Machines Corporation (IBM), a US-based technology company, launched the Watsonx platform, which is designed to power next-generation foundation models for businesses. The platform includes a studio for creating new models, generative AI and machine learning, a data store built on an open data lakehouse architecture, and a toolkit to speed up AI workflows. It allows organizations to train, adjust, and deploy AI models, including foundation models and machine learning capabilities, throughout their company with trusted data, speed, and governance, all in one location and across any cloud environment.

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Key Segments -

The machine learning as a service market covered in this report is segmented -

1) By Component: Solution, Services
2) By Organization: Small And Medium-Sized Enterprises, Large Enterprises
3) By Application: Marketing And Advertising, Fraud Detection And Risk Management, Computer Vision, Security And Surveillance, Predictive Analytics, Natural Language Processing, Augmented And Virtual Reality, Other Applications
4) By Industry Vertical: Banking, Financial Services And Insurance (BFSI), IT And Telecom, Automotive, Healthcare, Aerospace And Defense, Retail, Government, Other Industry Verticals

Key highlights covered in the report -
1. Detailed market size forecast and historical data analysis
2. Key drivers influencing market growth
3. Identification of upcoming trends and potential opportunities in the market
4. Analysis of major players strategies, to understand competitive dynamics and market positioning
5. Evaluation of regional dynamics

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