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市场调查报告书
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1551309

2030 年能源市场人工智慧预测：按组件类型、部署类型、应用、最终用户和地区进行的全球分析

AI in Energy Market Forecasts to 2030 - Global Analysis By Component Type (Hardware, Solutions and Services), Deployment Type (On-premise and Cloud-based), Application, End User and by Geography
出版日期: | 出版商: Stratistics Market Research Consulting | 英文 200+ Pages | 商品交期: 2-3个工作天内

价格

根据 Stratistics MRC 的数据，2024 年全球人工智慧能源市场规模将达到 68.1 亿美元，预计到 2030 年将达到 197.3 亿美元，预测期内复合年增长率为 19.4%。

人工智慧 (AI) 正在透过降低成本、提高效率和优化流程来改变能源产业。人工智慧 (AI) 技术被用来改善电网管理、预测能源需求并最大限度地提高能源产量。透过使用先进的演算法和机器学习来分析来自感测器和智慧电网的大量资料，人工智慧可以预测能源消耗模式并即时调整供应。此外，透过控制可再生能源波动、确保能源稳定供应，人工智慧将在可再生能源併网中发挥关键作用。

国际能源总署（IEA）表示，在能源领域采用人工智慧有可能显着提高能源效率，并实现更智慧的能源系统，能够即时适应不断变化的供需条件。

人们对能源效率的兴趣日益浓厚

随着全球能源消费量持续上升，对更有效的能源管理的需求不断增加。人工智慧 (AI) 技术在满足这一需求方面处于领先地位。人工智慧 (AI) 提供了预测能源消耗模式、最大化能源产出并减少能源浪费的工具。人工智慧 (AI) 能够使用机器学习演算法来识别能源系统的低效率、提案修改建议并对需求波动启动自动回应。此外，透过充分利用现有资源，我们不仅可以降低能源供应商的营运成本，还可以为全球减少温室气体排放的努力做出贡献。

实施成本过高

能源产业可以从人工智慧 (AI) 中受益匪浅，但许多组织（特别是小型公共产业和能源公司）发现实施人工智慧技术的初始成本遥不可及。整合人工智慧需要对软体、硬体和熟练的劳动力进行大量投资。升级您目前的基础设施、投资僱用和培训资料科学家和人工智慧专家、购买尖端感测器和资料处理设备等等都可以满足您公司的需求。此外，人工智慧演算法必须针对特定能源应用进行客製化，并且创建和维护成本高昂。

使用人工智慧建构预测维修系统

在人工智慧驱动的预测性维护方面，能源产业具有巨大的潜力。透过持续监控发电厂、输电线路和可再生能源设备等能源基础设施的健康状况，人工智慧 (AI) 可以在故障发生之前预测维护需求。除了降低维护成本外，还可以延长资产使用寿命并减少停机时间。此外，在预测性维护中使用人工智慧不仅可以提高营运效率，还可以提高能源生产和供应的安全性和可靠性。

网路安全威胁与风险

能源产业对人工智慧的依赖日益增加，存在重大的网路安全风险。人工智慧 (AI) 系统在控制发电厂、配电网路和能源网路方面变得越来越重要。对人工智慧主导的能源系统的成功攻击可能会导致大规模停电、关键基础设施受损，甚至对国家安全构成威胁。骇客可能能够修改人工智慧演算法，导致设备故障、危及能源发行或窃取敏感资讯。此外，随着能源系统变得更加数位化整合和依赖，攻击面将会扩大，网路攻击将变得更加难以防御。

COVID-19 的影响：

COVID-19 大流行对能源领域的人工智慧 (AI) 市场产生了重大影响。供应链中断、计划延误、封锁和经济成长放缓导致能源需求暂时下降。但疫情也加速了包括人工智慧 (AI) 在内的数位技术的采用，因为能源公司寻求简化业务、提高远端监控能力并为未来的衝击做好准备。此外，在危机期间，人们对人工智慧解决方案的兴趣增加，因为对更有效的能源管理和再生能源来源整合的需求变得更加强烈。

预计硬体领域将在预测期内成为最大的领域

预计硬体领域将占据能源领域人工智慧市场的最大份额。该部分包括实施人工智慧系统所需的零件，例如感测器、CPU、储存和其他关键基础设施。能源管理、智慧电网和可再生能源整合中的人工智慧应用需要可靠的资料收集、即时处理和储存能力，增加了对复杂硬体的需求。此外，能源公司现在已成为市场的主导部分，因为它们越来越多地采用人工智慧主导的解决方案，这推动了对复杂、高效能硬体的需求。

云端基础的细分市场预计在预测期内复合年增长率最高

能源市场人工智慧的云端基础的解决方案领域的复合年增长率最高。云端运算因其经济性、扩充性和灵活性而日益普及，是这一成长的关键驱动力。云端基础的人工智慧平台使能源公司能够利用大量资料和复杂的演算法，而无需太多的本地基础设施。此外，云端解决方案支援跨地理边界的协作并实现不同资料来源的集成，使组织能够管理复杂的能源系统并在能源优化和预测性维护等领域进行创新，这在促进方面特别有吸引力。

比最大的地区

北美在能源人工智慧市场中占有最大份额。这一优势得益于完善的能源部门、大量的研发投资以及最先进的技术基础设施。由于大量的公共和私人资金以及大型科技公司和创意新兴企业的强大存在，人工智慧技术的采用已成为北美，特别是美国的主要企业。此外，随着该地区专注于基础设施现代化、整合再生能源来源和提高能源效率，人工智慧解决方案的需求量很大。

复合年增长率最高的地区：

能源领域的人工智慧市场正以亚太地区最高的复合年增长率成长。该地区工业化程度的提高、能源和基础设施投资的增加以及旨在提高能源效率和引入再生能源来源的重大政府计划是这一快速增长的主要驱动力。中国和印度等国家正在製定采用人工智慧技术的标准，以满足不断增长的能源需求和更新能源系统。此外，智慧电网、都市化的发展和永续能源实践的推广也加速了人工智慧在该地区的采用。

免费客製化服务：

订阅此报告的客户可以存取以下免费自订选项之一：

  • 公司简介
    • 其他市场参与者的综合分析（最多 3 家公司）
    • 主要企业SWOT分析（最多3家企业）
  • 区域分割
    • 根据客户兴趣对主要国家的市场估计、预测和复合年增长率（註：基于可行性检查）
  • 竞争标基准化分析
    • 根据产品系列、地理分布和策略联盟对主要企业基准化分析

目录

第一章执行摘要

第二章 前言

  • 概述
  • 相关利益者
  • 调查范围
  • 调查方法
    • 资料探勘
    • 资料分析
    • 资料检验
    • 研究途径
  • 研究资讯来源
    • 主要研究资讯来源
    • 二次研究资讯来源
    • 先决条件

第三章市场趋势分析

  • 促进因素
  • 抑制因素
  • 机会
  • 威胁
  • 应用分析
  • 最终用户分析
  • 新兴市场
  • COVID-19 的影响

第4章波特五力分析

  • 供应商的议价能力
  • 买方议价能力
  • 替代品的威胁
  • 新进入者的威胁
  • 竞争公司之间的敌对关係

第五章全球能源人工智慧市场：按组件类型

  • 硬体
  • 解决方案
  • 服务

第六章全球能源人工智慧市场：按部署类型

  • 本地
  • 云端基础

第七章 全球能源人工智慧市场：依应用分类

  • 机器人技术
  • 能源管理
  • 可再生能源管理
  • 需求预测
  • 预测性维护
  • 网格最佳化
  • 安全保障
  • 基础设施
  • 其他用途

第八章 全球能源人工智慧市场：依最终用户分类

  • 发电
  • 石油和天然气
  • 可再生能源
  • 公共事业
  • 其他最终用户

第九章全球能源人工智慧市场：按地区

  • 北美洲
    • 美国
    • 加拿大
    • 墨西哥
  • 欧洲
    • 德国
    • 英国
    • 义大利
    • 法国
    • 西班牙
    • 其他欧洲国家
  • 亚太地区
    • 日本
    • 中国
    • 印度
    • 澳洲
    • 纽西兰
    • 韩国
    • 其他亚太地区
  • 南美洲
    • 阿根廷
    • 巴西
    • 智利
    • 南美洲其他地区
  • 中东/非洲
    • 沙乌地阿拉伯
    • 阿拉伯聯合大公国
    • 卡达
    • 南非
    • 其他中东和非洲

第10章 主要进展

  • 合约、伙伴关係、合作和合资企业
  • 收购和合併
  • 新产品发布
  • 业务拓展
  • 其他关键策略

第十一章 公司概况

  • Siemens AG
  • Hazama Ando Corporation
  • Amazon Web Services, Inc.
  • Informatec Ltd.
  • FlexGen Power Systems, Inc.
  • Schneider Electric
  • ABB Group
  • General Electric
  • SmartCloud Inc
  • AppOrchid Inc
  • Origami Energy Ltd.
  • Zen Robotics Ltd
  • Alpiq AG
Product Code: SMRC27092

According to Stratistics MRC, the Global AI in Energy Market is accounted for $6.81 billion in 2024 and is expected to reach $19.73 billion by 2030 growing at a CAGR of 19.4% during the forecast period. Artificial intelligence (AI) is transforming the energy industry through cost reduction, efficiency enhancement, and process optimization. Artificial intelligence (AI) technologies are being used to better manage distribution networks, forecast energy demand, and maximize energy production. AI is able to forecast patterns of energy consumption and make real-time adjustments to supply by analyzing large amounts of data from sensors and smart grids using sophisticated algorithms and machine learning. Furthermore, by controlling their variability and guaranteeing a steady supply of energy, AI plays a crucial role in the integration of renewable energy sources into the grid.

According to the International Energy Agency (IEA), the adoption of AI in the energy sector could lead to significant improvements in energy efficiency, enabling smarter energy systems that can adapt to changing demand and supply conditions in real-time.

Market Dynamics:

Driver:

Growing interest in energy efficiency

The demand for more effective energy management is growing as the world's energy consumption keeps rising. Leading the way in meeting this demand are artificial intelligence (AI) technologies, which provide tools to forecast patterns in energy consumption, maximize energy output, and cut down on needless energy spending. Artificial intelligence (AI) has the ability to recognize inefficiencies in energy systems, suggest modifications, and initiate automated reactions to variations in demand using machine learning algorithms. Moreover, by making the best use of the resources at hand, this not only lowers operating costs for energy providers but also helps the global effort to cut greenhouse gas emissions.

Restraint:

Exorbitant implementation expenses

The energy sector can benefit greatly from artificial intelligence (AI), but many organizations-especially smaller utilities and energy companies-may find the initial costs of implementing AI technologies to be unaffordable. Considerable investment in software, hardware, and qualified labor is needed for the integration of AI. Upgrading current infrastructure, investing in hiring or training data scientists and AI specialists, and buying cutting-edge sensors and data processing equipment are all possible needs for businesses. Additionally, AI algorithms must be customized for particular energy applications, which means that creating and maintaining them can be expensive.

Opportunity:

Creating AI-powered predictive maintenance systems

The energy sector has a lot of potential when it comes to AI-driven predictive maintenance. Through constant monitoring of the state of energy infrastructure, including power plants, transmission lines, and renewable energy installations, artificial intelligence (AI) can anticipate maintenance needs before a breakdown happens. In addition to lowering maintenance costs, this increases asset lifespan and decreases downtime. Furthermore, in addition to increasing operational effectiveness, the use of AI in predictive maintenance also increases safety and dependability in the generation and delivery of energy.

Threat:

Threats and risks to cybersecurity

There are major cybersecurity risks associated with the energy sector's growing reliance on AI. Artificial intelligence (AI) systems are becoming increasingly important for controlling power plants, distribution networks, and energy grids. Should an AI-driven energy system be successfully attacked, there could be widespread blackouts, harm to vital infrastructure, and even threats to national security. Hackers may be able to alter AI algorithms to cause equipment malfunctions, compromise energy distribution, or pilfer confidential information. Moreover, the attack surface grows as energy systems become more digitally integrated and dependent, increasing the difficulty of defending against cyber attacks.

Covid-19 Impact:

The COVID-19 pandemic had a significant effect on artificial intelligence (AI) in the energy market. It caused supply chain disruptions, project delays, and a brief decline in energy demand as a result of lockdowns and slower economic growth. But as energy companies looked to streamline operations, improve remote monitoring capabilities, and fortify themselves against future shocks, the pandemic also hastened the adoption of digital technologies, including artificial intelligence (AI). Additionally, interest in AI solutions increased during the crisis as the need for more effective energy management and the integration of renewable energy sources became even more imperative.

The Hardware segment is expected to be the largest during the forecast period

In the AI in Energy market, the hardware segment is projected to hold the largest share. Parts like sensors, CPUs, storage, and other vital infrastructure are included in this segment that is necessary for implementing AI systems. Because AI applications in energy management, smart grids, and renewable energy integration require reliable data collection, real-time processing, and storage capabilities, there is an increasing need for sophisticated hardware. Furthermore, energy companies are now the dominant segment in the market due to their increasing adoption of AI-driven solutions, which is driving up demand for sophisticated and high-performance hardware.

The Cloud-based segment is expected to have the highest CAGR during the forecast period

The AI in Energy market's cloud-based solutions segment has the highest CAGR. The growing popularity of cloud computing due to its affordability, scalability, and flexibility is the main driver of this growth. Energy companies can now use large amounts of data and sophisticated algorithms without requiring a lot of on-premise infrastructure owing to cloud-based AI platforms. Moreover, cloud solutions support collaboration across geographical boundaries and enable the integration of disparate data sources, which makes them especially appealing for managing complex energy systems and fostering innovation in fields like energy optimization and predictive maintenance.

Region with largest share:

In the AI in Energy market, North America has the largest share. A well-established energy sector, significant investments in research and development, and the region's cutting-edge technological infrastructure are all credited for this dominance. The adoption of AI technologies is leading in North America, especially the US, owing to the substantial funding from the public and private sectors, as well as the strong presence of large technology companies and creative start-ups. Additionally, AI solutions are in high demand because of the region's emphasis on modernizing infrastructure, integrating renewable energy sources, and increasing energy efficiency.

Region with highest CAGR:

The AI in Energy market is growing at the highest CAGR in the Asia-Pacific region. The region's growing industrialization, rising energy infrastructure investment, and major government programs to improve energy efficiency and incorporate renewable energy sources are the main drivers of this fast growth. In order to meet their increasing energy demands and update their energy systems, nations like China and India are setting the standard for the adoption of AI technologies. Furthermore, the adoption of AI in the region is also accelerating due to the development of smart grids, urbanization, and the push for sustainable energy practices.

Key players in the market

Some of the key players in AI in Energy market include Siemens AG, Hazama Ando Corporation, Amazon Web Services, Inc., Informatec Ltd., FlexGen Power Systems, Inc., Schneider Electric, ABB Group, General Electric, SmartCloud Inc, AppOrchid Inc, Origami Energy Ltd., Zen Robotics Ltd and Alpiq AG.

Key Developments:

In July 2024, Boson Energy and Siemens AG have signed a Memorandum of Understanding (MoU) to facilitate collaboration on technology that converts non-recyclable waste into clean energy. The collaboration aims to advance sustainable, local energy security, enabling hydrogen-powered electric vehicle charging infrastructure without compromising grid stability or impacting consumer prices.

In November 2023, Battery storage system integrator FlexGen and battery manufacturer Hithium could be supplying each other with complementary technologies for large-scale battery energy storage system (BESS) projects. FlexGen would buy up to 10GWh of Hithium battery capacity in that time, while the Chinese manufacturer would use FlexGen's energy management system (EMS) in a combined 15GWh of projects.

In November 2023, Schneider Electric, the leader in the digital transformation of energy management and automation, today announced at its Capital Markets Day meeting with investors a $3 billion multi-year agreement with Compass Datacenters. The agreement extends the companies' existing relationship that integrates their respective supply chains to manufacture and deliver prefabricated modular data center solutions.

Component Types Covered:

  • Hardware
  • Solutions
  • Services

Deployment Types Covered:

  • On-premise
  • Cloud-based

Applications Covered:

  • Robotics
  • Energy Management
  • Renewables Management
  • Demand Forecasting
  • Predictive Maintenance
  • Grid Optimization
  • Safety and Security
  • Infrastructure
  • Other Applications

End Users Covered:

  • Power Generation
  • Oil & Gas
  • Renewable Energy
  • Utilities
  • Other End Users

Regions Covered:

  • North America
    • US
    • Canada
    • Mexico
  • Europe
    • Germany
    • UK
    • Italy
    • France
    • Spain
    • Rest of Europe
  • Asia Pacific
    • Japan
    • China
    • India
    • Australia
    • New Zealand
    • South Korea
    • Rest of Asia Pacific
  • South America
    • Argentina
    • Brazil
    • Chile
    • Rest of South America
  • Middle East & Africa
    • Saudi Arabia
    • UAE
    • Qatar
    • South Africa
    • Rest of Middle East & Africa

What our report offers:

  • Market share assessments for the regional and country-level segments
  • Strategic recommendations for the new entrants
  • Covers Market data for the years 2022, 2023, 2024, 2026, and 2030
  • Market Trends (Drivers, Constraints, Opportunities, Threats, Challenges, Investment Opportunities, and recommendations)
  • Strategic recommendations in key business segments based on the market estimations
  • Competitive landscaping mapping the key common trends
  • Company profiling with detailed strategies, financials, and recent developments
  • Supply chain trends mapping the latest technological advancements

Free Customization Offerings:

All the customers of this report will be entitled to receive one of the following free customization options:

  • Company Profiling
    • Comprehensive profiling of additional market players (up to 3)
    • SWOT Analysis of key players (up to 3)
  • Regional Segmentation
    • Market estimations, Forecasts and CAGR of any prominent country as per the client's interest (Note: Depends on feasibility check)
  • Competitive Benchmarking
    • Benchmarking of key players based on product portfolio, geographical presence, and strategic alliances

Table of Contents

1 Executive Summary

2 Preface

  • 2.1 Abstract
  • 2.2 Stake Holders
  • 2.3 Research Scope
  • 2.4 Research Methodology
    • 2.4.1 Data Mining
    • 2.4.2 Data Analysis
    • 2.4.3 Data Validation
    • 2.4.4 Research Approach
  • 2.5 Research Sources
    • 2.5.1 Primary Research Sources
    • 2.5.2 Secondary Research Sources
    • 2.5.3 Assumptions

3 Market Trend Analysis

  • 3.1 Introduction
  • 3.2 Drivers
  • 3.3 Restraints
  • 3.4 Opportunities
  • 3.5 Threats
  • 3.6 Application Analysis
  • 3.7 End User Analysis
  • 3.8 Emerging Markets
  • 3.9 Impact of Covid-19

4 Porters Five Force Analysis

  • 4.1 Bargaining power of suppliers
  • 4.2 Bargaining power of buyers
  • 4.3 Threat of substitutes
  • 4.4 Threat of new entrants
  • 4.5 Competitive rivalry

5 Global AI in Energy Market, By Component Type

  • 5.1 Introduction
  • 5.2 Hardware
  • 5.3 Solutions
  • 5.4 Services

6 Global AI in Energy Market, By Deployment Type

  • 6.1 Introduction
  • 6.2 On-premise
  • 6.3 Cloud-based

7 Global AI in Energy Market, By Application

  • 7.1 Introduction
  • 7.2 Robotics
  • 7.3 Energy Management
  • 7.4 Renewables Management
  • 7.5 Demand Forecasting
  • 7.6 Predictive Maintenance
  • 7.7 Grid Optimization
  • 7.8 Safety and Security
  • 7.9 Infrastructure
  • 7.10 Other Applications

8 Global AI in Energy Market, By End User

  • 8.1 Introduction
  • 8.2 Power Generation
  • 8.3 Oil & Gas
  • 8.4 Renewable Energy
  • 8.5 Utilities
  • 8.6 Other End Users

9 Global AI in Energy Market, By Geography

  • 9.1 Introduction
  • 9.2 North America
    • 9.2.1 US
    • 9.2.2 Canada
    • 9.2.3 Mexico
  • 9.3 Europe
    • 9.3.1 Germany
    • 9.3.2 UK
    • 9.3.3 Italy
    • 9.3.4 France
    • 9.3.5 Spain
    • 9.3.6 Rest of Europe
  • 9.4 Asia Pacific
    • 9.4.1 Japan
    • 9.4.2 China
    • 9.4.3 India
    • 9.4.4 Australia
    • 9.4.5 New Zealand
    • 9.4.6 South Korea
    • 9.4.7 Rest of Asia Pacific
  • 9.5 South America
    • 9.5.1 Argentina
    • 9.5.2 Brazil
    • 9.5.3 Chile
    • 9.5.4 Rest of South America
  • 9.6 Middle East & Africa
    • 9.6.1 Saudi Arabia
    • 9.6.2 UAE
    • 9.6.3 Qatar
    • 9.6.4 South Africa
    • 9.6.5 Rest of Middle East & Africa

10 Key Developments

  • 10.1 Agreements, Partnerships, Collaborations and Joint Ventures
  • 10.2 Acquisitions & Mergers
  • 10.3 New Product Launch
  • 10.4 Expansions
  • 10.5 Other Key Strategies

11 Company Profiling

  • 11.1 Siemens AG
  • 11.2 Hazama Ando Corporation
  • 11.3 Amazon Web Services, Inc.
  • 11.4 Informatec Ltd.
  • 11.5 FlexGen Power Systems, Inc.
  • 11.6 Schneider Electric
  • 11.7 ABB Group
  • 11.8 General Electric
  • 11.9 SmartCloud Inc
  • 11.10 AppOrchid Inc
  • 11.11 Origami Energy Ltd.
  • 11.12 Zen Robotics Ltd
  • 11.13 Alpiq AG

List of Tables

  • Table 1 Global AI in Energy Market Outlook, By Region (2022-2030) ($MN)
  • Table 2 Global AI in Energy Market Outlook, By Component Type (2022-2030) ($MN)
  • Table 3 Global AI in Energy Market Outlook, By Hardware (2022-2030) ($MN)
  • Table 4 Global AI in Energy Market Outlook, By Solutions (2022-2030) ($MN)
  • Table 5 Global AI in Energy Market Outlook, By Services (2022-2030) ($MN)
  • Table 6 Global AI in Energy Market Outlook, By Deployment Type (2022-2030) ($MN)
  • Table 7 Global AI in Energy Market Outlook, By On-premise (2022-2030) ($MN)
  • Table 8 Global AI in Energy Market Outlook, By Cloud-based (2022-2030) ($MN)
  • Table 9 Global AI in Energy Market Outlook, By Application (2022-2030) ($MN)
  • Table 10 Global AI in Energy Market Outlook, By Robotics (2022-2030) ($MN)
  • Table 11 Global AI in Energy Market Outlook, By Energy Management (2022-2030) ($MN)
  • Table 12 Global AI in Energy Market Outlook, By Renewables Management (2022-2030) ($MN)
  • Table 13 Global AI in Energy Market Outlook, By Demand Forecasting (2022-2030) ($MN)
  • Table 14 Global AI in Energy Market Outlook, By Predictive Maintenance (2022-2030) ($MN)
  • Table 15 Global AI in Energy Market Outlook, By Grid Optimization (2022-2030) ($MN)
  • Table 16 Global AI in Energy Market Outlook, By Safety and Security (2022-2030) ($MN)
  • Table 17 Global AI in Energy Market Outlook, By Infrastructure (2022-2030) ($MN)
  • Table 18 Global AI in Energy Market Outlook, By Other Applications (2022-2030) ($MN)
  • Table 19 Global AI in Energy Market Outlook, By End User (2022-2030) ($MN)
  • Table 20 Global AI in Energy Market Outlook, By Power Generation (2022-2030) ($MN)
  • Table 21 Global AI in Energy Market Outlook, By Oil & Gas (2022-2030) ($MN)
  • Table 22 Global AI in Energy Market Outlook, By Renewable Energy (2022-2030) ($MN)
  • Table 23 Global AI in Energy Market Outlook, By Utilities (2022-2030) ($MN)
  • Table 24 Global AI in Energy Market Outlook, By Other End Users (2022-2030) ($MN)
  • Table 25 North America AI in Energy Market Outlook, By Country (2022-2030) ($MN)
  • Table 26 North America AI in Energy Market Outlook, By Component Type (2022-2030) ($MN)
  • Table 27 North America AI in Energy Market Outlook, By Hardware (2022-2030) ($MN)
  • Table 28 North America AI in Energy Market Outlook, By Solutions (2022-2030) ($MN)
  • Table 29 North America AI in Energy Market Outlook, By Services (2022-2030) ($MN)
  • Table 30 North America AI in Energy Market Outlook, By Deployment Type (2022-2030) ($MN)
  • Table 31 North America AI in Energy Market Outlook, By On-premise (2022-2030) ($MN)
  • Table 32 North America AI in Energy Market Outlook, By Cloud-based (2022-2030) ($MN)
  • Table 33 North America AI in Energy Market Outlook, By Application (2022-2030) ($MN)
  • Table 34 North America AI in Energy Market Outlook, By Robotics (2022-2030) ($MN)
  • Table 35 North America AI in Energy Market Outlook, By Energy Management (2022-2030) ($MN)
  • Table 36 North America AI in Energy Market Outlook, By Renewables Management (2022-2030) ($MN)
  • Table 37 North America AI in Energy Market Outlook, By Demand Forecasting (2022-2030) ($MN)
  • Table 38 North America AI in Energy Market Outlook, By Predictive Maintenance (2022-2030) ($MN)
  • Table 39 North America AI in Energy Market Outlook, By Grid Optimization (2022-2030) ($MN)
  • Table 40 North America AI in Energy Market Outlook, By Safety and Security (2022-2030) ($MN)
  • Table 41 North America AI in Energy Market Outlook, By Infrastructure (2022-2030) ($MN)
  • Table 42 North America AI in Energy Market Outlook, By Other Applications (2022-2030) ($MN)
  • Table 43 North America AI in Energy Market Outlook, By End User (2022-2030) ($MN)
  • Table 44 North America AI in Energy Market Outlook, By Power Generation (2022-2030) ($MN)
  • Table 45 North America AI in Energy Market Outlook, By Oil & Gas (2022-2030) ($MN)
  • Table 46 North America AI in Energy Market Outlook, By Renewable Energy (2022-2030) ($MN)
  • Table 47 North America AI in Energy Market Outlook, By Utilities (2022-2030) ($MN)
  • Table 48 North America AI in Energy Market Outlook, By Other End Users (2022-2030) ($MN)
  • Table 49 Europe AI in Energy Market Outlook, By Country (2022-2030) ($MN)
  • Table 50 Europe AI in Energy Market Outlook, By Component Type (2022-2030) ($MN)
  • Table 51 Europe AI in Energy Market Outlook, By Hardware (2022-2030) ($MN)
  • Table 52 Europe AI in Energy Market Outlook, By Solutions (2022-2030) ($MN)
  • Table 53 Europe AI in Energy Market Outlook, By Services (2022-2030) ($MN)
  • Table 54 Europe AI in Energy Market Outlook, By Deployment Type (2022-2030) ($MN)
  • Table 55 Europe AI in Energy Market Outlook, By On-premise (2022-2030) ($MN)
  • Table 56 Europe AI in Energy Market Outlook, By Cloud-based (2022-2030) ($MN)
  • Table 57 Europe AI in Energy Market Outlook, By Application (2022-2030) ($MN)
  • Table 58 Europe AI in Energy Market Outlook, By Robotics (2022-2030) ($MN)
  • Table 59 Europe AI in Energy Market Outlook, By Energy Management (2022-2030) ($MN)
  • Table 60 Europe AI in Energy Market Outlook, By Renewables Management (2022-2030) ($MN)
  • Table 61 Europe AI in Energy Market Outlook, By Demand Forecasting (2022-2030) ($MN)
  • Table 62 Europe AI in Energy Market Outlook, By Predictive Maintenance (2022-2030) ($MN)
  • Table 63 Europe AI in Energy Market Outlook, By Grid Optimization (2022-2030) ($MN)
  • Table 64 Europe AI in Energy Market Outlook, By Safety and Security (2022-2030) ($MN)
  • Table 65 Europe AI in Energy Market Outlook, By Infrastructure (2022-2030) ($MN)
  • Table 66 Europe AI in Energy Market Outlook, By Other Applications (2022-2030) ($MN)
  • Table 67 Europe AI in Energy Market Outlook, By End User (2022-2030) ($MN)
  • Table 68 Europe AI in Energy Market Outlook, By Power Generation (2022-2030) ($MN)
  • Table 69 Europe AI in Energy Market Outlook, By Oil & Gas (2022-2030) ($MN)
  • Table 70 Europe AI in Energy Market Outlook, By Renewable Energy (2022-2030) ($MN)
  • Table 71 Europe AI in Energy Market Outlook, By Utilities (2022-2030) ($MN)
  • Table 72 Europe AI in Energy Market Outlook, By Other End Users (2022-2030) ($MN)
  • Table 73 Asia Pacific AI in Energy Market Outlook, By Country (2022-2030) ($MN)
  • Table 74 Asia Pacific AI in Energy Market Outlook, By Component Type (2022-2030) ($MN)
  • Table 75 Asia Pacific AI in Energy Market Outlook, By Hardware (2022-2030) ($MN)
  • Table 76 Asia Pacific AI in Energy Market Outlook, By Solutions (2022-2030) ($MN)
  • Table 77 Asia Pacific AI in Energy Market Outlook, By Services (2022-2030) ($MN)
  • Table 78 Asia Pacific AI in Energy Market Outlook, By Deployment Type (2022-2030) ($MN)
  • Table 79 Asia Pacific AI in Energy Market Outlook, By On-premise (2022-2030) ($MN)
  • Table 80 Asia Pacific AI in Energy Market Outlook, By Cloud-based (2022-2030) ($MN)
  • Table 81 Asia Pacific AI in Energy Market Outlook, By Application (2022-2030) ($MN)
  • Table 82 Asia Pacific AI in Energy Market Outlook, By Robotics (2022-2030) ($MN)
  • Table 83 Asia Pacific AI in Energy Market Outlook, By Energy Management (2022-2030) ($MN)
  • Table 84 Asia Pacific AI in Energy Market Outlook, By Renewables Management (2022-2030) ($MN)
  • Table 85 Asia Pacific AI in Energy Market Outlook, By Demand Forecasting (2022-2030) ($MN)
  • Table 86 Asia Pacific AI in Energy Market Outlook, By Predictive Maintenance (2022-2030) ($MN)
  • Table 87 Asia Pacific AI in Energy Market Outlook, By Grid Optimization (2022-2030) ($MN)
  • Table 88 Asia Pacific AI in Energy Market Outlook, By Safety and Security (2022-2030) ($MN)
  • Table 89 Asia Pacific AI in Energy Market Outlook, By Infrastructure (2022-2030) ($MN)
  • Table 90 Asia Pacific AI in Energy Market Outlook, By Other Applications (2022-2030) ($MN)
  • Table 91 Asia Pacific AI in Energy Market Outlook, By End User (2022-2030) ($MN)
  • Table 92 Asia Pacific AI in Energy Market Outlook, By Power Generation (2022-2030) ($MN)
  • Table 93 Asia Pacific AI in Energy Market Outlook, By Oil & Gas (2022-2030) ($MN)
  • Table 94 Asia Pacific AI in Energy Market Outlook, By Renewable Energy (2022-2030) ($MN)
  • Table 95 Asia Pacific AI in Energy Market Outlook, By Utilities (2022-2030) ($MN)
  • Table 96 Asia Pacific AI in Energy Market Outlook, By Other End Users (2022-2030) ($MN)
  • Table 97 South America AI in Energy Market Outlook, By Country (2022-2030) ($MN)
  • Table 98 South America AI in Energy Market Outlook, By Component Type (2022-2030) ($MN)
  • Table 99 South America AI in Energy Market Outlook, By Hardware (2022-2030) ($MN)
  • Table 100 South America AI in Energy Market Outlook, By Solutions (2022-2030) ($MN)
  • Table 101 South America AI in Energy Market Outlook, By Services (2022-2030) ($MN)
  • Table 102 South America AI in Energy Market Outlook, By Deployment Type (2022-2030) ($MN)
  • Table 103 South America AI in Energy Market Outlook, By On-premise (2022-2030) ($MN)
  • Table 104 South America AI in Energy Market Outlook, By Cloud-based (2022-2030) ($MN)
  • Table 105 South America AI in Energy Market Outlook, By Application (2022-2030) ($MN)
  • Table 106 South America AI in Energy Market Outlook, By Robotics (2022-2030) ($MN)
  • Table 107 South America AI in Energy Market Outlook, By Energy Management (2022-2030) ($MN)
  • Table 108 South America AI in Energy Market Outlook, By Renewables Management (2022-2030) ($MN)
  • Table 109 South America AI in Energy Market Outlook, By Demand Forecasting (2022-2030) ($MN)
  • Table 110 South America AI in Energy Market Outlook, By Predictive Maintenance (2022-2030) ($MN)
  • Table 111 South America AI in Energy Market Outlook, By Grid Optimization (2022-2030) ($MN)
  • Table 112 South America AI in Energy Market Outlook, By Safety and Security (2022-2030) ($MN)
  • Table 113 South America AI in Energy Market Outlook, By Infrastructure (2022-2030) ($MN)
  • Table 114 South America AI in Energy Market Outlook, By Other Applications (2022-2030) ($MN)
  • Table 115 South America AI in Energy Market Outlook, By End User (2022-2030) ($MN)
  • Table 116 South America AI in Energy Market Outlook, By Power Generation (2022-2030) ($MN)
  • Table 117 South America AI in Energy Market Outlook, By Oil & Gas (2022-2030) ($MN)
  • Table 118 South America AI in Energy Market Outlook, By Renewable Energy (2022-2030) ($MN)
  • Table 119 South America AI in Energy Market Outlook, By Utilities (2022-2030) ($MN)
  • Table 120 South America AI in Energy Market Outlook, By Other End Users (2022-2030) ($MN)
  • Table 121 Middle East & Africa AI in Energy Market Outlook, By Country (2022-2030) ($MN)
  • Table 122 Middle East & Africa AI in Energy Market Outlook, By Component Type (2022-2030) ($MN)
  • Table 123 Middle East & Africa AI in Energy Market Outlook, By Hardware (2022-2030) ($MN)
  • Table 124 Middle East & Africa AI in Energy Market Outlook, By Solutions (2022-2030) ($MN)
  • Table 125 Middle East & Africa AI in Energy Market Outlook, By Services (2022-2030) ($MN)
  • Table 126 Middle East & Africa AI in Energy Market Outlook, By Deployment Type (2022-2030) ($MN)
  • Table 127 Middle East & Africa AI in Energy Market Outlook, By On-premise (2022-2030) ($MN)
  • Table 128 Middle East & Africa AI in Energy Market Outlook, By Cloud-based (2022-2030) ($MN)
  • Table 129 Middle East & Africa AI in Energy Market Outlook, By Application (2022-2030) ($MN)
  • Table 130 Middle East & Africa AI in Energy Market Outlook, By Robotics (2022-2030) ($MN)
  • Table 131 Middle East & Africa AI in Energy Market Outlook, By Energy Management (2022-2030) ($MN)
  • Table 132 Middle East & Africa AI in Energy Market Outlook, By Renewables Management (2022-2030) ($MN)
  • Table 133 Middle East & Africa AI in Energy Market Outlook, By Demand Forecasting (2022-2030) ($MN)
  • Table 134 Middle East & Africa AI in Energy Market Outlook, By Predictive Maintenance (2022-2030) ($MN)
  • Table 135 Middle East & Africa AI in Energy Market Outlook, By Grid Optimization (2022-2030) ($MN)
  • Table 136 Middle East & Africa AI in Energy Market Outlook, By Safety and Security (2022-2030) ($MN)
  • Table 137 Middle East & Africa AI in Energy Market Outlook, By Infrastructure (2022-2030) ($MN)
  • Table 138 Middle East & Africa AI in Energy Market Outlook, By Other Applications (2022-2030) ($MN)
  • Table 139 Middle East & Africa AI in Energy Market Outlook, By End User (2022-2030) ($MN)
  • Table 140 Middle East & Africa AI in Energy Market Outlook, By Power Generation (2022-2030) ($MN)
  • Table 141 Middle East & Africa AI in Energy Market Outlook, By Oil & Gas (2022-2030) ($MN)
  • Table 142 Middle East & Africa AI in Energy Market Outlook, By Renewable Energy (2022-2030) ($MN)
  • Table 143 Middle East & Africa AI in Energy Market Outlook, By Utilities (2022-2030) ($MN)
  • Table 144 Middle East & Africa AI in Energy Market Outlook, By Other End Users (2022-2030) ($MN)