Abstract
Summary
LPI (LP Information)' newest research report, the “Machine Learning in Utilities Industry Forecast” looks at past sales and reviews total world Machine Learning in Utilities sales in 2022, providing a comprehensive analysis by region and market sector of projected Machine Learning in Utilities sales for 2023 through 2029. With Machine Learning in Utilities sales broken down by region, market sector and sub-sector, this report provides a detailed analysis in US$ millions of the world Machine Learning in Utilities industry.
This Insight Report provides a comprehensive analysis of the global Machine Learning in Utilities landscape and highlights key trends related to product segmentation, company formation, revenue, and market share, latest development, and M&A activity. This report also analyzes the strategies of leading global companies with a focus on Machine Learning in Utilities portfolios and capabilities, market entry strategies, market positions, and geographic footprints, to better understand these firms’ unique position in an accelerating global Machine Learning in Utilities market.
This Insight Report evaluates the key market trends, drivers, and affecting factors shaping the global outlook for Machine Learning in Utilities and breaks down the forecast by type, by application, geography, and market size to highlight emerging pockets of opportunity. With a transparent methodology based on hundreds of bottom-up qualitative and quantitative market inputs, this study forecast offers a highly nuanced view of the current state and future trajectory in the global Machine Learning in Utilities.
The global Machine Learning in Utilities market size is projected to grow from US$ million in 2022 to US$ million in 2029; it is expected to grow at a CAGR of % from 2023 to 2029.
United States market for Machine Learning in Utilities is estimated to increase from US$ million in 2022 to US$ million by 2029, at a CAGR of % from 2023 through 2029.
China market for Machine Learning in Utilities is estimated to increase from US$ million in 2022 to US$ million by 2029, at a CAGR of % from 2023 through 2029.
Europe market for Machine Learning in Utilities is estimated to increase from US$ million in 2022 to US$ million by 2029, at a CAGR of % from 2023 through 2029.
Global key Machine Learning in Utilities players cover Baidu, Hewlett Packard Enterprise Development LP, SAS Institute, Inc., IBM, Microsoft, Nvidia, Amazon Web Services, Oracle and SAP, etc. In terms of revenue, the global two largest companies occupied for a share nearly % in 2022.
This report presents a comprehensive overview, market shares, and growth opportunities of Machine Learning in Utilities market by product type, application, key players and key regions and countries.
Market Segmentation:
Segmentation by type
Hardware
Software
Service
Segmentation by application
Renewable Energy Management
Demand Forecast
Safety and Security
Infrastructure
Other
This report also splits the market by region:
Americas
United States
Canada
Mexico
Brazil
APAC
China
Japan
Korea
Southeast Asia
India
Australia
Europe
Germany
France
UK
Italy
Russia
Middle East & Africa
Egypt
South Africa
Israel
Turkey
GCC Countries
The below companies that are profiled have been selected based on inputs gathered from primary experts and analyzing the company's coverage, product portfolio, its market penetration.
Baidu
Hewlett Packard Enterprise Development LP
SAS Institute, Inc.
IBM
Microsoft
Nvidia
Amazon Web Services
Oracle
SAP
BigML, Inc.
Fair Isaac Corporation
Intel Corporation
Google LLC
H2o.AI
Alpiq
SmartCloud
This Insight Report provides a comprehensive analysis of the global Machine Learning in Utilities landscape and highlights key trends related to product segmentation, company formation, revenue, and market share, latest development, and M&A activity. This report also analyzes the strategies of leading global companies with a focus on Machine Learning in Utilities portfolios and capabilities, market entry strategies, market positions, and geographic footprints, to better understand these firms’ unique position in an accelerating global Machine Learning in Utilities market.
This Insight Report evaluates the key market trends, drivers, and affecting factors shaping the global outlook for Machine Learning in Utilities and breaks down the forecast by type, by application, geography, and market size to highlight emerging pockets of opportunity. With a transparent methodology based on hundreds of bottom-up qualitative and quantitative market inputs, this study forecast offers a highly nuanced view of the current state and future trajectory in the global Machine Learning in Utilities.
The global Machine Learning in Utilities market size is projected to grow from US$ million in 2022 to US$ million in 2029; it is expected to grow at a CAGR of % from 2023 to 2029.
United States market for Machine Learning in Utilities is estimated to increase from US$ million in 2022 to US$ million by 2029, at a CAGR of % from 2023 through 2029.
China market for Machine Learning in Utilities is estimated to increase from US$ million in 2022 to US$ million by 2029, at a CAGR of % from 2023 through 2029.
Europe market for Machine Learning in Utilities is estimated to increase from US$ million in 2022 to US$ million by 2029, at a CAGR of % from 2023 through 2029.
Global key Machine Learning in Utilities players cover Baidu, Hewlett Packard Enterprise Development LP, SAS Institute, Inc., IBM, Microsoft, Nvidia, Amazon Web Services, Oracle and SAP, etc. In terms of revenue, the global two largest companies occupied for a share nearly % in 2022.
This report presents a comprehensive overview, market shares, and growth opportunities of Machine Learning in Utilities market by product type, application, key players and key regions and countries.
Market Segmentation:
Segmentation by type
Hardware
Software
Service
Segmentation by application
Renewable Energy Management
Demand Forecast
Safety and Security
Infrastructure
Other
This report also splits the market by region:
Americas
United States
Canada
Mexico
Brazil
APAC
China
Japan
Korea
Southeast Asia
India
Australia
Europe
Germany
France
UK
Italy
Russia
Middle East & Africa
Egypt
South Africa
Israel
Turkey
GCC Countries
The below companies that are profiled have been selected based on inputs gathered from primary experts and analyzing the company's coverage, product portfolio, its market penetration.
Baidu
Hewlett Packard Enterprise Development LP
SAS Institute, Inc.
IBM
Microsoft
Nvidia
Amazon Web Services
Oracle
SAP
BigML, Inc.
Fair Isaac Corporation
Intel Corporation
Google LLC
H2o.AI
Alpiq
SmartCloud
Table of Contents
1 Scope of the Report
1.1 Market Introduction
1.2 Years Considered
1.3 Research Objectives
1.4 Market Research Methodology
1.5 Research Process and Data Source
1.6 Economic Indicators
1.7 Currency Considered
1.8 Market Estimation Caveats
2 Executive Summary
2.1 World Market Overview
2.1.1 Global Machine Learning in Utilities Market Size 2018-2029
2.1.2 Machine Learning in Utilities Market Size CAGR by Region 2018 VS 2022 VS 2029
2.2 Machine Learning in Utilities Segment by Type
2.2.1 Hardware
2.2.2 Software
2.2.3 Service
2.3 Machine Learning in Utilities Market Size by Type
2.3.1 Machine Learning in Utilities Market Size CAGR by Type (2018 VS 2022 VS 2029)
2.3.2 Global Machine Learning in Utilities Market Size Market Share by Type (2018-2023)
2.4 Machine Learning in Utilities Segment by Application
2.4.1 Renewable Energy Management
2.4.2 Demand Forecast
2.4.3 Safety and Security
2.4.4 Infrastructure
2.4.5 Other
2.5 Machine Learning in Utilities Market Size by Application
2.5.1 Machine Learning in Utilities Market Size CAGR by Application (2018 VS 2022 VS 2029)
2.5.2 Global Machine Learning in Utilities Market Size Market Share by Application (2018-2023)
3 Machine Learning in Utilities Market Size by Player
3.1 Machine Learning in Utilities Market Size Market Share by Players
3.1.1 Global Machine Learning in Utilities Revenue by Players (2018-2023)
3.1.2 Global Machine Learning in Utilities Revenue Market Share by Players (2018-2023)
3.2 Global Machine Learning in Utilities Key Players Head office and Products Offered
3.3 Market Concentration Rate Analysis
3.3.1 Competition Landscape Analysis
3.3.2 Concentration Ratio (CR3, CR5 and CR10) & (2021-2023)
3.4 New Products and Potential Entrants
3.5 Mergers & Acquisitions, Expansion
4 Machine Learning in Utilities by Regions
4.1 Machine Learning in Utilities Market Size by Regions (2018-2023)
4.2 Americas Machine Learning in Utilities Market Size Growth (2018-2023)
4.3 APAC Machine Learning in Utilities Market Size Growth (2018-2023)
4.4 Europe Machine Learning in Utilities Market Size Growth (2018-2023)
4.5 Middle East & Africa Machine Learning in Utilities Market Size Growth (2018-2023)
5 Americas
5.1 Americas Machine Learning in Utilities Market Size by Country (2018-2023)
5.2 Americas Machine Learning in Utilities Market Size by Type (2018-2023)
5.3 Americas Machine Learning in Utilities Market Size by Application (2018-2023)
5.4 United States
5.5 Canada
5.6 Mexico
5.7 Brazil
6 APAC
6.1 APAC Machine Learning in Utilities Market Size by Region (2018-2023)
6.2 APAC Machine Learning in Utilities Market Size by Type (2018-2023)
6.3 APAC Machine Learning in Utilities Market Size by Application (2018-2023)
6.4 China
6.5 Japan
6.6 Korea
6.7 Southeast Asia
6.8 India
6.9 Australia
7 Europe
7.1 Europe Machine Learning in Utilities by Country (2018-2023)
7.2 Europe Machine Learning in Utilities Market Size by Type (2018-2023)
7.3 Europe Machine Learning in Utilities Market Size by Application (2018-2023)
7.4 Germany
7.5 France
7.6 UK
7.7 Italy
7.8 Russia
8 Middle East & Africa
8.1 Middle East & Africa Machine Learning in Utilities by Region (2018-2023)
8.2 Middle East & Africa Machine Learning in Utilities Market Size by Type (2018-2023)
8.3 Middle East & Africa Machine Learning in Utilities Market Size by Application (2018-2023)
8.4 Egypt
8.5 South Africa
8.6 Israel
8.7 Turkey
8.8 GCC Countries
9 Market Drivers, Challenges and Trends
9.1 Market Drivers & Growth Opportunities
9.2 Market Challenges & Risks
9.3 Industry Trends
10 Global Machine Learning in Utilities Market Forecast
10.1 Global Machine Learning in Utilities Forecast by Regions (2024-2029)
10.1.1 Global Machine Learning in Utilities Forecast by Regions (2024-2029)
10.1.2 Americas Machine Learning in Utilities Forecast
10.1.3 APAC Machine Learning in Utilities Forecast
10.1.4 Europe Machine Learning in Utilities Forecast
10.1.5 Middle East & Africa Machine Learning in Utilities Forecast
10.2 Americas Machine Learning in Utilities Forecast by Country (2024-2029)
10.2.1 United States Machine Learning in Utilities Market Forecast
10.2.2 Canada Machine Learning in Utilities Market Forecast
10.2.3 Mexico Machine Learning in Utilities Market Forecast
10.2.4 Brazil Machine Learning in Utilities Market Forecast
10.3 APAC Machine Learning in Utilities Forecast by Region (2024-2029)
10.3.1 China Machine Learning in Utilities Market Forecast
10.3.2 Japan Machine Learning in Utilities Market Forecast
10.3.3 Korea Machine Learning in Utilities Market Forecast
10.3.4 Southeast Asia Machine Learning in Utilities Market Forecast
10.3.5 India Machine Learning in Utilities Market Forecast
10.3.6 Australia Machine Learning in Utilities Market Forecast
10.4 Europe Machine Learning in Utilities Forecast by Country (2024-2029)
10.4.1 Germany Machine Learning in Utilities Market Forecast
10.4.2 France Machine Learning in Utilities Market Forecast
10.4.3 UK Machine Learning in Utilities Market Forecast
10.4.4 Italy Machine Learning in Utilities Market Forecast
10.4.5 Russia Machine Learning in Utilities Market Forecast
10.5 Middle East & Africa Machine Learning in Utilities Forecast by Region (2024-2029)
10.5.1 Egypt Machine Learning in Utilities Market Forecast
10.5.2 South Africa Machine Learning in Utilities Market Forecast
10.5.3 Israel Machine Learning in Utilities Market Forecast
10.5.4 Turkey Machine Learning in Utilities Market Forecast
10.5.5 GCC Countries Machine Learning in Utilities Market Forecast
10.6 Global Machine Learning in Utilities Forecast by Type (2024-2029)
10.7 Global Machine Learning in Utilities Forecast by Application (2024-2029)
11 Key Players Analysis
11.1 Baidu
11.1.1 Baidu Company Information
11.1.2 Baidu Machine Learning in Utilities Product Offered
11.1.3 Baidu Machine Learning in Utilities Revenue, Gross Margin and Market Share (2018-2023)
11.1.4 Baidu Main Business Overview
11.1.5 Baidu Latest Developments
11.2 Hewlett Packard Enterprise Development LP
11.2.1 Hewlett Packard Enterprise Development LP Company Information
11.2.2 Hewlett Packard Enterprise Development LP Machine Learning in Utilities Product Offered
11.2.3 Hewlett Packard Enterprise Development LP Machine Learning in Utilities Revenue, Gross Margin and Market Share (2018-2023)
11.2.4 Hewlett Packard Enterprise Development LP Main Business Overview
11.2.5 Hewlett Packard Enterprise Development LP Latest Developments
11.3 SAS Institute, Inc.
11.3.1 SAS Institute, Inc. Company Information
11.3.2 SAS Institute, Inc. Machine Learning in Utilities Product Offered
11.3.3 SAS Institute, Inc. Machine Learning in Utilities Revenue, Gross Margin and Market Share (2018-2023)
11.3.4 SAS Institute, Inc. Main Business Overview
11.3.5 SAS Institute, Inc. Latest Developments
11.4 IBM
11.4.1 IBM Company Information
11.4.2 IBM Machine Learning in Utilities Product Offered
11.4.3 IBM Machine Learning in Utilities Revenue, Gross Margin and Market Share (2018-2023)
11.4.4 IBM Main Business Overview
11.4.5 IBM Latest Developments
11.5 Microsoft
11.5.1 Microsoft Company Information
11.5.2 Microsoft Machine Learning in Utilities Product Offered
11.5.3 Microsoft Machine Learning in Utilities Revenue, Gross Margin and Market Share (2018-2023)
11.5.4 Microsoft Main Business Overview
11.5.5 Microsoft Latest Developments
11.6 Nvidia
11.6.1 Nvidia Company Information
11.6.2 Nvidia Machine Learning in Utilities Product Offered
11.6.3 Nvidia Machine Learning in Utilities Revenue, Gross Margin and Market Share (2018-2023)
11.6.4 Nvidia Main Business Overview
11.6.5 Nvidia Latest Developments
11.7 Amazon Web Services
11.7.1 Amazon Web Services Company Information
11.7.2 Amazon Web Services Machine Learning in Utilities Product Offered
11.7.3 Amazon Web Services Machine Learning in Utilities Revenue, Gross Margin and Market Share (2018-2023)
11.7.4 Amazon Web Services Main Business Overview
11.7.5 Amazon Web Services Latest Developments
11.8 Oracle
11.8.1 Oracle Company Information
11.8.2 Oracle Machine Learning in Utilities Product Offered
11.8.3 Oracle Machine Learning in Utilities Revenue, Gross Margin and Market Share (2018-2023)
11.8.4 Oracle Main Business Overview
11.8.5 Oracle Latest Developments
11.9 SAP
11.9.1 SAP Company Information
11.9.2 SAP Machine Learning in Utilities Product Offered
11.9.3 SAP Machine Learning in Utilities Revenue, Gross Margin and Market Share (2018-2023)
11.9.4 SAP Main Business Overview
11.9.5 SAP Latest Developments
11.10 BigML, Inc.
11.10.1 BigML, Inc. Company Information
11.10.2 BigML, Inc. Machine Learning in Utilities Product Offered
11.10.3 BigML, Inc. Machine Learning in Utilities Revenue, Gross Margin and Market Share (2018-2023)
11.10.4 BigML, Inc. Main Business Overview
11.10.5 BigML, Inc. Latest Developments
11.11 Fair Isaac Corporation
11.11.1 Fair Isaac Corporation Company Information
11.11.2 Fair Isaac Corporation Machine Learning in Utilities Product Offered
11.11.3 Fair Isaac Corporation Machine Learning in Utilities Revenue, Gross Margin and Market Share (2018-2023)
11.11.4 Fair Isaac Corporation Main Business Overview
11.11.5 Fair Isaac Corporation Latest Developments
11.12 Intel Corporation
11.12.1 Intel Corporation Company Information
11.12.2 Intel Corporation Machine Learning in Utilities Product Offered
11.12.3 Intel Corporation Machine Learning in Utilities Revenue, Gross Margin and Market Share (2018-2023)
11.12.4 Intel Corporation Main Business Overview
11.12.5 Intel Corporation Latest Developments
11.13 Google LLC
11.13.1 Google LLC Company Information
11.13.2 Google LLC Machine Learning in Utilities Product Offered
11.13.3 Google LLC Machine Learning in Utilities Revenue, Gross Margin and Market Share (2018-2023)
11.13.4 Google LLC Main Business Overview
11.13.5 Google LLC Latest Developments
11.14 H2o.AI
11.14.1 H2o.AI Company Information
11.14.2 H2o.AI Machine Learning in Utilities Product Offered
11.14.3 H2o.AI Machine Learning in Utilities Revenue, Gross Margin and Market Share (2018-2023)
11.14.4 H2o.AI Main Business Overview
11.14.5 H2o.AI Latest Developments
11.15 Alpiq
11.15.1 Alpiq Company Information
11.15.2 Alpiq Machine Learning in Utilities Product Offered
11.15.3 Alpiq Machine Learning in Utilities Revenue, Gross Margin and Market Share (2018-2023)
11.15.4 Alpiq Main Business Overview
11.15.5 Alpiq Latest Developments
11.16 SmartCloud
11.16.1 SmartCloud Company Information
11.16.2 SmartCloud Machine Learning in Utilities Product Offered
11.16.3 SmartCloud Machine Learning in Utilities Revenue, Gross Margin and Market Share (2018-2023)
11.16.4 SmartCloud Main Business Overview
11.16.5 SmartCloud Latest Developments
12 Research Findings and Conclusion