Machine Learning as a Service (MLaaS) Market Innovations, Applications,Growth Analysis, Demand Insights by 2030

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The global Machine Learning (ML) market size is expected to reach USD 183.89 Billion in 2030 and register a revenue CAGR of 44.1% during the forecast period.

Extensive adoption of smartphones, e-commerce, and social media due to rising penetration of the Internet is driving machine learning market revenue growth

Market Size – USD 4.73 Billion in 2020, Market Growth – at a CAGR of 44.1%, Market Trend – Increasing investment in RD

New York, January 25,2022-The global Machine Learning (ML) market size is expected to reach USD 183.89 Billion in 2030 and register a revenue CAGR of 44.1% over the forecast period, according to latest report by Reports and Data. Rising trend of integrating cloud computing with systems and Bring Your Own Device (BYOD) work model, coupled with continuous technological advancements is driving machine learning market revenue growth.

Machine learning helps in analyzing large volumes of data and identifying specific trends and patterns that would not be apparent otherwise. For instance, for an e-commerce website such as Amazon, it helps to analyze purchase histories and browsing behaviors of its users, which in turn, helps in catering to the right opportunities, products, and reminders relevant to users. The results are then used to provide appropriate advertisements to users. Machine learning enables systems to learn, make predictions, and improve algorithms. For example, anti-virus software learns to filter new threats as they are recognized. Algorithms can handle data that are multi-dimensional and multi-variety, even in dynamic or uncertain environments.

Virtual agents are another important trend driving demand for machine learning. Virtual agents respond to customers through emails or chatbots on company websites and thus, provide human-like customized help to clients. Companies such as Google and Amazon are providing 24/7 customer services using virtual agents. Virtual agents rely on Artificial Intelligence (AI) systems to answer customer queries. AI systems depend on machine learning to establish and analyze frequently asked questions. Machine learning is expected to enable robots to perform business management tasks in the coming years. Algorithms are a powerful tool for pattern recognition and predictive analytics. Robots will be able to perform repetitive tasks, which are currently being done by lower-level managers, with the help of algorithms. Such advancements are expected to have a positive impact on market growth.

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 Some Key Highlights from the Report

  • In January 2022, Amazon and Stellantis collaborated to introduce customer-centric connected experiences across millions of vehicles, thereby helping to 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.
  • Software segment accounted for a larger revenue share in 2020. Data can be examined, analyzed, and then decisions can be made with the help of software.
  • Small and medium-sized enterprises are increasingly adopting machine learning tools to reduce investments in Information and Communications Technology (ICT) and access digital resources. Rapid digitalization and increase in cyber threats are driving growth of small and medium-sized enterprises segment.
  • Fraud detection risk analytics has been a significant concern for the banking and financial industry. Increasing number of transactions owing to a plethora of payment channels, such as smartphones, credit/debit cards, and others, are increasing chances of fraud. As a result, it is becoming difficult for businesses to authenticate their transactions, which is creating demand for advanced technologies such as machine learning to resolve such issues.
  • Predictive maintenance segment is expected to register a high revenue growth rate during the forecast period. Manufacturing firms need corrective as well as preventive maintenance practices in place. However, these practices are often inefficient and expensive. Machine learning helps in the creation of highly efficient predictive maintenance programs. These can minimize chances of unexpected failures, thereby reducing unnecessary preventive maintenance projects.
  • BFSI segment accounted for a significant revenue share in 2020. Some common benefits provided by machine learning to the BFSI industry include algorithmic trading, portfolio management, loan underwriting, and most importantly, fraud detection. Also, the technology facilitates continual data assessment for detecting and analyzing anomalies and nuances. This helps in improving accuracy of financial models and rules.
  • Market in North America accounted for largest revenue share in 2020. The region is rapidly adopting machine learning technology and is investing heavily in newer technologies like artificial intelligence, cloud computing, and others. Generation of vast amounts of data through social media and IT companies is increasing demand for advanced technologies like machine learning. Rising adoption of autonomous vehicles and presence of key market players investing in RD of machine learning are also driving revenue growth of the North America market.
  • Companies profiled in the global market report include Oracle Corporation, International Business Machines (IBM) Corporation, Amazon Web Services, Inc., Microsoft Corporation, Fractal Analytics Inc., Google LLC, Baidu Inc., Intel Corporation, Hewlett Packard Enterprise Development LP, and Dell Inc.

For this report, Reports and Data has segmented the global Machine Learning (ML) market based on component, organization size, application, end-use, and region:

Component Outlook (Revenue, USD Billion; 2018–2030)

  • Software
    • Access Control
    • Security Intelligence
    • Big Data Governance
    • Cloud and Web-based Application Programming Interface (APIs)
    • Others
  • Services
    • Managed Services
    • Professional Services
      • Support Maintenance
      • Support Integration
      • Training

Organization Size Outlook (Revenue, USD Billion; 2018–2030)

  • Small and Medium-Sized Enterprises
  • Large Enterprises

Application Outlook (Revenue, USD Billion; 2018–2030)

  • Fraud Detection Risk Analytics
  • Augmented Virtual reality
  • Natural Language processing
  • Computer vision
  • Security surveillance
  • Marketing Advertisement
  • Automated Network Management
  • Predictive Maintenance
  • Others

End-use Outlook (Revenue, USD Billion; 2018–2030)

  • Automotive
  • Aerospace Defense
  • Retail E-commerce
  • Government
  • Healthcare And Life Sciences
  • Media Entertainment
  • IT And Telecommunications
  • BFSI
  • Others

Regional Outlook (Revenue, USD Billion; 2018–2030)

  • North America
    • U.S.
    • Canada
    • Mexico
  • Europe
    • Germany
    • U.K.
    • France
    • Italy
    • Spain
    • Sweden
    • BENELUX
    • Rest of Europe
  • Asia-Pacific
    • China
    • India
    • Japan
    • South Korea
    • Rest of APAC
  • Latin America
    • Brazil
    • Rest of LATAM
  • Middle East Africa
    • Saudi Arabia
    • UAE
    • South Africa
    • Israel
    • Rest of MEA

Key Advantages of Machine Learning as a Service (MLaaS) Report:

  • Identification and analysis of the market size and competition
  • Qualitative and quantitative analysis of the market data
  • Data validated by industry experts after extensive primary and secondary research
  • Extensive regional analysis of the Machine Learning as a Service (MLaaS) industry
  • Profiling of key players along with their business overview, business strategies, deals and partnerships, and product portfolio
  • SWOT and Porter’s Five Forces Analysis for in-depth understanding of the competitive landscape
  • Feasibility analysis and investment analysis to enable strategic investment decisions
  • Analysis of opportunities, drivers, restraints, challenges, risks, and limitations

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