NEW YORK, May 11, 2023 /PRNewswire/ -- The machine learning market size o grow by USD 56,493.47 million at a CAGR of 47.81% from 2022 to 2027, according to the latest research report from Technavio. The research report focuses on top companies and crucial drivers, current growth dynamics, futuristic opportunities, and new product/project launches. Discover IT Consulting & Other Services industry potential and make informed business decisions based on qualitative and quantitative evidence highlighted in Technavio reports. View Sample Report

Vendor Landscape

The machine learning market is fragmented. Many local and global vendors offer machine learning with limited product differentiation. However, due to the significant growth of the market, vendors are continuously adopting the latest innovations. Therefore, the threat of rivalry was low, and it is expected to remain the same during the forecast period. Some of the key vendors covered in the report include:

• Alibaba Group Holding Ltd. - The company offers machine learning platforms for AI that rely on Alibaba Cloud distributed computing clusters.

• Alphabet Inc. - The company offers innovative machine learning products and services that will help build, deploy, and scale more effective AI models.

• Amazon.com Inc. - The company offers SageMaker which is a machine learning service enabling data scientists, data engineers, MLOps engineers, and business analysts to build, train, and deploy ML models for any use case, regardless of ML expertise.

• BigML Inc. - The company offers machine learning which provides predictive applications across industries including aerospace, automotive, energy, entertainment, financial services, food, healthcare, IoT, pharmaceutical, transportation, and telecommunications.

• Altair Engineering Inc.

• Alteryx Inc.

• Cisco Systems Inc.

• Fair Isaac Corp.

• H2O.ai Inc.

• Hewlett Packard Enterprise Co.

• Iflowsoft Solutions Inc.

• Intel Corp.

• International Business Machines Corp.

• Microsoft Corp.

• Netguru S.A

• Salesforce.com Inc.

• SAP SE

• SAS Institute Inc.

• TIBCO Software Inc.

• Yottamine Analytics LLC

For the market's vendor landscape highlights with a comprehensive list of vendors and
their offerings - View Sample Report

Key Market Segmentation

The market is segmented by end-user (BFSI, retail, telecommunications, healthcare, and automotive and others), deployment (cloud-based and on-premise), and geography (North America, Europe, APAC, Middle East and Africa, and South America).

By end-user, the market will observe significant growth in the BFSI segment during the forecast period. BFSI companies are increasingly adopting machine learning solutions to understand their customers and provide customized solutions. The adoption of machine learning solutions is helping BFSI companies in achieving automated processing, data-driven insights about customers, and personalized customer outreach. In addition, the ongoing digital transformation initiatives in the BFSI sector has been driving the growth of the segment.

View Sample Report for more highlights into the market segments.

Regional Market Outlook

North America will account for 36% of the market growth during the forecast period. The growth of the regional market is driven by the increase in data generation from industries such as telecommunications, manufacturing, retail, and energy. Also, the increasing need to ensure data consistency and accuracy, improve data quality, identify data patterns, detect anomalies, and develop predictions among enterprises is another major factor driving the growth of the machine learning market in North America.

For more key highlights on the regional market share of most of the above-mentioned
countries. - View Sample Report

The machine learning market covers the following areas:

• Machine Learning Market Sizing

• Machine Learning Market Forecast

• Machine Learning Market Analysis

Market Dynamics

• Driver – The market is driven by the increasing adoption of cloud-based offerings. Cloud-based services solutions offer various benefits such as minimal cost for computing, network and storage infrastructure, scalability, reliability, and high resource availability. Cloud-based solutions eliminate the need for dedicated IT support teams and hence reduces operating costs. Many such benefits are increasing the adoption of cloud-based offerings among enterprises. Machine learning solutions helps enterprises to scale up the production workload of their projects over cloud with the increase in data. Thus, the increased adoption of cloud-based offerings will drive the growth of the market during the forecast period.

• Trend – The growing number of acquisitions and partnerships is identified as the key trend in the market. Vendors operating in the market are focused on forming strategic alliances with other players to gain a competitive advantage. These growth strategies are allowing vendors to gain access to new clients. Strategic partnerships also provide access to a larger customer base and technologies to help them improve their product portfolio. Moreover, partnerships and acquisitions help vendors to expand their presence in new markets. This trend among vendors will have a positive influence on the market growth over the forecast period.

• Challenge – The shortage of skilled professionals is identified as the major challenge hindering market growth. Most enterprises lack a proper mix of AI and machine learning skillset-based workforce. This has led enterprises to invest more time and money in retaining and training their existing employees. Also, companies working and investing in AI and machine learning face challenges in finding skilled workforces. Such challenges are restricting the growth of the market in focus.

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Key Topics Covered:

1 Executive Summary

• 1.1 Market overview

2 Market Landscape

• 2.1 Market ecosystem

3 Market Sizing

• 3.1 Market definition

• 3.2 Market segment analysis

• 3.3 Market size 2022

• 3.4 Market outlook: Forecast for 2022-2027

4 Historic Market Size

• 4.1 Global machine learning market 2017 - 2021

• 4.2 End-User Segment Analysis 2017 - 2021

• 4.3 Deployment Segment Analysis 2017 - 2021

• 4.4 Geography Segment Analysis 2017 - 2021

• 4.5 Country Segment Analysis 2017 - 2021

5 Five Forces Analysis

• 5.1 Five forces summary

• 5.2 Bargaining power of buyers

• 5.3 Bargaining power of suppliers

• 5.4 Threat of new entrants

• 5.5 Threat of substitutes

• 5.6 Threat of rivalry

• 5.7 Market condition

6 Market Segmentation by End-user

• 6.1 Market segments

• 6.2 Comparison by End-user

• 6.3 BFSI - Market size and forecast 2022-2027

• 6.4 Retail - Market size and forecast 2022-2027

• 6.5 Telecommunications - Market size and forecast 2022-2027

• 6.6 Healthcare - Market size and forecast 2022-2027

• 6.7 Automotive and others - Market size and forecast 2022-2027

• 6.8 Market opportunity by End-user

7 Market Segmentation by Deployment

• 7.1 Market segments

• 7.2 Comparison by Deployment

• 7.3 Cloud-based - Market size and forecast 2022-2027

• 7.4 On-premise - Market size and forecast 2022-2027

• 7.5 Market opportunity by Deployment

8 Customer Landscape

• 8.1 Customer landscape overview

9 Geographic Landscape

• 9.1 Geographic segmentation

• 9.2 Geographic comparison

• 9.3 North America - Market size and forecast 2022-2027

• 9.4 Europe - Market size and forecast 2022-2027

• 9.5 APAC - Market size and forecast 2022-2027

• 9.6 Middle East and Africa - Market size and forecast 2022-2027

• 9.7 South America - Market size and forecast 2022-2027

• 9.8 US - Market size and forecast 2022-2027

• 9.9 China - Market size and forecast 2022-2027

• 9.10 UK - Market size and forecast 2022-2027

• 9.11 Germany - Market size and forecast 2022-2027

• 9.12 Japan - Market size and forecast 2022-2027

• 9.13 Market opportunity by geography

10 Drivers, Challenges, and Trends

• 10.1 Market drivers

• 10.2 Market challenges

• 10.3 Impact of drivers and challenges

• 10.4 Market trends

11 Vendor Landscape

• 11.1 Overview

• 11.2 Vendor landscape

• 11.3 Landscape disruption

• 11.4 Industry risks

12 Vendor Analysis

• 12.1 Vendors covered

• 12.2 Market positioning of vendors

• 12.3 Alibaba Group Holding Ltd.

• 12.4 Alphabet Inc.

• 12.5 Amazon.com Inc.

• 12.6 BigML Inc.

• 12.7 Cisco Systems Inc.

• 12.8 Fair Isaac Corp.

• 12.9 H2O.ai Inc.

• 12.10 Hewlett Packard Enterprise Co.

• 12.11 Iflowsoft Solutions Inc.

• 12.12 Intel Corp.

• 12.13 International Business Machines Corp.

• 12.14 Microsoft Corp.

• 12.15 Salesforce.com Inc.

• 12.16 SAP SE

• 12.17 SAS Institute Inc.

13 Appendix

• 13.1 Scope of the report

• 13.2 Inclusions and exclusions checklist

• 13.3 Currency conversion rates for US$

• 13.4 Research methodology

• 13.5 List of abbreviations

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