AI in Energy Management Market Industry - Opportunity Analysis and Growth Forecast to 2024 - ResearchAndMarkets.com

DUBLIN--(BUSINESS WIRE)--The "AI in Energy Management Market Research Report: By Type, Solution, Application, Technology, End User - Industry Opportunity Analysis and Growth Forecast to 2024" report has been added to ResearchAndMarkets.com's offering.

From $4,439.1 million in 2018, the artificial intelligence (AI) in energy management market is projected to grow to $12,200.9 million in 2024, at a 19.8% CAGR during 2019-2024 (forecast period).

Based on end user, the market was dominated by the utility category, in 2018, as AI solutions are being deployed by numerous companies, including Dominion Energy Inc. and Duke Energy Corporation, to bridge the gap between the demand and supply of electricity.

The most significant trend being observed in the AI in energy management market is the integration of internet of things (IoT) in energy management systems (EMS). IoT provides remote control, software automation, data insights, and proactive monitoring, in EMSs. It uses smart sensors and meters, installed in production lines as well as machines, to alert users about the amount of energy being consumed. Additionally, with the complete package of services and software IoT offers, energy costs can be reduced substantially.

The use of AI to make the grid more efficient is a major AI in energy management market growth driver. A grid is a complex system of wires, transformers, and other infrastructure components, through which electricity is transported over long distance. Such infrastructure differs vastly in complexity and size; it can be for a single building, an entire nation, or one which distributes energy across countries and continents, in which case it is called a transcontinental grid.

The power in the grid comes from a variety of sources, including fossil-fuel-based power plants, solar panel installations, wind power plants, hydroelectricity plants, as well as nuclear power stations, which makes their operation a cumbersome process. With AI analyzing the massive volumes of data generated from their operations on a daily basis, they become stable and energy-efficient, thereby driving the AI in energy management market growth.

Key Topics Covered:

Chapter 1. Research Background

1.1 Research Objectives

1.2 Market Definition

1.3 Research Scope

1.3.1 Market Segmentation by Deployment Type

1.3.2 Market Segmentation by Solution

1.3.3 Market Segmentation by Application

1.3.4 Market Segmentation by Technology

1.3.5 Market Segmentation by End User

1.3.6 Market Segmentation by Region

1.3.7 Analysis Period

1.3.8 Market Data Reporting Unit

1.3.8.1 Value

1.4 Key Stakeholders

Chapter 2. Research Methodology

2.1 Secondary Research

2.2 Primary Research

2.2.1 Breakdown of Primary Research Respondents

2.2.1.1 By region

2.2.1.2 By industry participant

2.2.1.3 By company type

2.3 Market Size Estimation

2.4 Data Triangulation

2.5 Assumptions for the Study

Chapter 3. Executive Summary

Chapter 4. Introduction

4.1 Definition of Market Segments

4.2 Value Chain Analysis

4.3 Market Dynamics

4.3.1 Trends

4.3.2 Drivers

4.3.3 Restraints

4.3.4 Opportunities

Chapter 5. Global Market Size and Forecast

5.1 By Deployment Type

5.2 By Solution

5.3 By Application

5.3.1 Energy Output Forecasting, By Type

5.4 By Technology

5.5 By End User

5.6 By Region

Chapter 6. North America Market Size and Forecast

6.1 By Deployment Type

6.2 By Solution

6.3 By Application

Chapter 7. Europe Market Size and Forecast

7.1 By Deployment Type

7.2 By Solution

7.3 By Application

Chapter 8. APAC Market Size and Forecast

8.1 By Deployment Type

8.2 By Solution

8.3 By Application

Chapter 9. LATAM Market Size and Forecast

9.1 By Deployment Type

9.2 By Solution

9.3 By Application

Chapter 10. MEA Market Size and Forecast

10.1 By Deployment Type

10.2 By Solution

10.3 By Application

Chapter 11. Competitive Landscape

11.1 List of Key Players and Offerings

11.2 Market Share Analysis of Key Players

11.3 Competitive Benchmarking of Key Players

11.4 Strategic Developments of Key Players

11.4.1 Mergers and Acquisitions

11.4.2 Partnerships

11.4.3 Product Launches

11.4.4 Geographic Expansion

11.4.5 Client Wins

Chapter 12. Company Profiles

12.1 General Electric Company

12.2 ABB Ltd.

12.3 Siemens AG

12.4 Schneider Electric SE

12.5 Mitsubishi Electric Corporation

12.6 Eaton Corporation plc

12.7 Alphabet Inc.

12.8 Honeywell International Inc.

12.9 International Business Machines (IBM) Corporation

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