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市场调查报告书
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1677288

能源市场人工智慧按组件、技术类型、应用领域和最终用户划分 - 2025 年至 2030 年全球预测

Artificial Intelligence in Energy Market by Component, Technology Types, Application Areas, End User - Global Forecast 2025-2030
出版日期: | 出版商: 360iResearch | 英文 196 Pages | 商品交期: 最快1-2个工作天内

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能源领域的人工智慧市场规模预计在 2024 年将达到 99.2 亿美元，2025 年将达到 123.6 亿美元，复合年增长率为 25.37%，到 2030 年将达到 385.5 亿美元。

主要市场统计数据
基准年 2024 年 99.2亿美元
预计 2025 年 123.6亿美元
预测年份 2030 385.5亿美元
复合年增长率（%） 25.37％

人工智慧正快速重塑能源格局，带来业务效率、策略规划、系统可靠性等方面的深刻变化。近年来，先进的机器学习技术与能源管理方法的整合带来了巨大的机会。能源公司正在利用人工智慧来最大限度地减少低效率，并透过更智慧的电网管理和预测性维护来推动永续性。重新关注能源领域的数位转型也推动了能源需求和供应预测更强大的分析，使营运商能够更好地应对动态的市场条件。

人工智慧在能源领域的重要性日益增加，从优化发电到实现对电网健康状况的即时监控。从可再生能源的整合到传统发电厂的运营，该行业的每个方面都受益于资料主导的洞察。这种动态不仅带来了绩效的提高，而且还带来了优先考虑永续性和弹性的新经营模式。能源相关人员越来越多地投资于人工智慧解决方案，以释放先前未开发的营运智慧蕴藏量，而高阶分析则推动集体成本节约和增强决策能力。

本报告全面介绍了人工智慧如何改变能源产业。它详细介绍了决策者可以采取的关键创新、不断发展的市场结构和现实策略。在数位科技决定竞争力的时代，了解人工智慧在能源生产、分配和消费中的作用至关重要。以下我们将深入探讨推动这些技术进步的变革性转变、细分细节、区域差异和主要企业。

重新定义能源格局的转型

随着数位化的进步和人工智慧的日益普及，能源产业正在经历前所未有的变化，并显着转向技术主导的解决方案。在过去的十年中，传统方法逐渐让位给优化电网管理和增强能源储存解决方案的创新预测系统。这种转变是多方面压力的结果，包括不断增长的能源需求、环境限制和全球对可再生能源整合的推动。

数位转型推动了能源领域的操作技术和资讯技术的融合。强大的机器学习模型已成为主流，使组织能够更准确地预测消费模式，即时分析资产绩效，并显着减少非计划性停机时间。在这种情况下，重点是采取主动方法，将重点从被动解决方案转移到预测问题并在问题变得严重之前缓解问题。

自动控制系统和智慧感测器的引入使企业能够从海量资料中获得可行的见解。电脑视觉、自然语言处理和机器人技术的整合不仅实现了常规流程的自动化，还提高了安全性和业务效率。此外，在决策流程中采用尖端的人工智慧技术重新定义了营运基准，并为能源发行的可靠性和效率设定了新的标准。这些变革性转变正在影响当今的投资策略、营运规划和公共，标誌着产业发展的关键曲折点。

市场成长的关键细分洞察

市场区隔提供了多样化的视角来评估人工智慧在能源领域的影响。在组件层面，透过硬体、服务和软体的互动来探索市场。硬体解决方案包括先进的控制器、强大的处理器和复杂的感测器阵列，有助于跨能源网路的资料采集。服务组件包括咨询服务、部署和整合专业知识以及强大的支援和维护框架，以确保您的系统无缝运作。软体部门涵盖分析解决方案和综合能源管理软体，强调资料解释和敏捷控制机制在现代能源营运中的重要性。

为了进一步细分，我们需要了解技术类型。此观点主要关注电脑视觉、机器学习、自然语言处理和机器人等专业应用。在电脑视觉领域，影像识别和视讯分析功能是增强监控和资产追踪的驱动力。机器学习细分为强化学习、监督学习和无监督学习。这些调查方法增强了预测分析和自适应系统反应。同样，自然语言处理涵盖语言翻译和高级语音辨识，有助于增强控制室的人机介面。

按应用领域细分市场可以提供更深入的见解。这包括需求面管理、能源管理、电网管理和预测性维护等关键领域。需求面管理显示需求预测和能源效率优化等因素极为重要。能源管理将变得更加细緻入微，需量反应、能源交易和负载预测策略使营运商能够平衡波动的消费者需求和供应。电网管理强调电网监控和微电网开发的重要性，而预测性维护则着重于状态监控和故障前预测，以减少停机时间。

最后，最终用户的分析揭示了影响市场动态的人口统计多样化需求模式。商业建筑的目标是办公大楼和购物中心，而工业应用则涵盖采矿、石油和天然气等领域。在住宅应用方面，该报告重点关注能源储存系统和智慧家庭创新的兴起，使最终用户能够有效地管理消费量。公共产业部门透过检查配电系统营运商和发电公司，进一步细分其在能源生态系统中的作用。这种全面的细分有助于了解频谱的人工智慧应用，并客製化解决方案以有效满足特定的市场需求。

目录

第 1 章 简介

第二章调查方法

第三章执行摘要

第四章 市场概况

第五章 市场洞察

  • 市场动态
    • 驱动程式
      • 人工智慧智慧电网技术的应用不断扩大，以提高能源效率和永续性目标
      • 对人工智慧驱动的预测性维护解决方案的需求不断增加，以降低能源基础设施的营运成本
    • 限制因素
      • 高昂的实施成本和复杂的整合流程限制了人工智慧在能源系统中的应用
    • 机会
      • 开发人工智慧能源储存解决方案，解决再生能源来源的间歇性问题
      • 扩大人工智慧在可再生能源管理的应用，以优化资源利用率和电网稳定性
    • 任务
      • 资料隐私问题和监管不确定性影响人工智慧在能源应用中的扩充性
  • 市场区隔分析
    • 组件：驱动能源领域人工智慧系统的硬体组件
    • 最终用户：工业领域用于能源优化的人工智慧应用
  • 波特五力分析
  • PESTEL 分析
    • 政治的
    • 经济
    • 社会的
    • 技术的
    • 合法的
    • 环境

第六章 能源领域人工智慧市场（按组成部分）

  • 硬体
    • 控制器
    • 处理器
    • 感应器
  • 服务
    • 咨询服务
    • 部署和集成
    • 支援和维护
  • 软体
    • 分析解决方案
    • 能源管理软体

第七章 能源市场中的人工智慧（依技术类型）

  • 电脑视觉
    • 影像识别
    • 影片分析
  • 机器学习
    • 强化学习
    • 监督学习
    • 无监督学习
  • 自然语言处理
    • 语言翻译
    • 语音辨识
  • 机器人

第 8 章 能源领域人工智慧市场（按应用）

  • 需求面管理
    • 需求预测
    • 优化能源效率
  • 能源管理
    • 需量反应
    • 能源交易
    • 负荷预测
  • 电网管理
    • 电网监控
    • 微型电网
  • 预测性维护
    • 状态监测
    • 故障预测

第九章 能源领域人工智慧市场（按最终用户划分）

  • 商业的
    • 办公大楼
    • 购物中心
  • 产业
    • 矿业
    • 石油和天然气
  • 住宅
    • 能源储存系统
    • 智慧家庭
  • 实用工具
    • 配电公司
    • 发电公司

第 10 章 美洲能源领域人工智慧市场

  • 阿根廷
  • 巴西
  • 加拿大
  • 墨西哥
  • 美国

第 11 章 亚太能源领域人工智慧市场

  • 澳洲
  • 中国
  • 印度
  • 印尼
  • 日本
  • 马来西亚
  • 菲律宾
  • 新加坡
  • 韩国
  • 台湾
  • 泰国
  • 越南

第 12 章。

  • 丹麦
  • 埃及
  • 芬兰
  • 法国
  • 德国
  • 以色列
  • 义大利
  • 荷兰
  • 奈及利亚
  • 挪威
  • 波兰
  • 卡达
  • 俄罗斯
  • 沙乌地阿拉伯
  • 南非
  • 西班牙
  • 瑞典
  • 瑞士
  • 土耳其
  • 阿拉伯聯合大公国
  • 英国

第十三章 竞争格局

  • 2024 年市场占有率分析
  • FPNV 定位矩阵，2024 年
  • 竞争情境分析
  • 战略分析与建议

公司列表

  • ABB Ltd.
  • C3.ai, Inc.
  • Eaton Corporation
  • ENEL Group
  • Engie SA
  • General Electric Company
  • Google, LLC
  • Grid4C
  • Honeywell International Inc.
  • IBM Corporation
  • Microsoft Corporation
  • Mitsubishi Electric Corporation
  • NextEra Energy, Inc.
  • Nokia Corporation
  • Saudi Arabian Oil Co.
  • Schneider Electric
  • Siemens AG
  • Uplight, Inc.
  • Uptake Technologies, Inc.
  • Verdigris Technologies
Product Code: MRR-5319A8C1C0D8

The Artificial Intelligence in Energy Market was valued at USD 9.92 billion in 2024 and is projected to grow to USD 12.36 billion in 2025, with a CAGR of 25.37%, reaching USD 38.55 billion by 2030.

KEY MARKET STATISTICS
Base Year [2024] USD 9.92 billion
Estimated Year [2025] USD 12.36 billion
Forecast Year [2030] USD 38.55 billion
CAGR (%) 25.37%

Artificial Intelligence is rapidly reshaping the energy landscape, driving profound changes across operational efficiency, strategic planning, and system reliability. In recent years, the confluence of advanced machine learning techniques with energy management practices has unlocked significant opportunities. Energy companies are harnessing AI to minimize inefficiencies and drive sustainability through smarter grid management and predictive maintenance. The renewed focus on digital transformation across energy assets also promotes robust analytics in forecasting energy demand and supply, ensuring that operators can better respond to dynamic market conditions.

The growing importance of AI in energy extends from optimizing power generation to enabling real-time monitoring of grid health. Every aspect of the sector, from renewable energy integration to legacy power plant operations, benefits from data-driven insights. This dynamic has not only led to performance improvements but also to new business models that prioritize sustainability and resilience. Energy stakeholders are increasingly investing in AI solutions that unlock previously untapped reserves of operational intelligence, while advanced analytics facilitate lump-sum cost savings and enhanced decision-making.

This report provides a comprehensive exploration of how AI is transforming the energy domain. It details critical innovations, evolving market structures, and pragmatic strategies that decision-makers can adopt. In an era where digital technologies dictate competitive edge, understanding the role of AI in energy production, distribution, and consumption is paramount. The discussion below delves into transformative shifts, segmentation details, regional disparities, and the leading companies that are driving these technological advancements.

Transformative Shifts Redefining the Energy Landscape

The energy sector has witnessed unprecedented changes driven by advanced digitalization and the increasing adoption of artificial intelligence, marking a notable shift toward technology-led solutions. Over the past decade, traditional methodologies are gradually giving way to innovative predictive systems that optimize grid management and enhance energy storage solutions. This transformation is a result of multi-faceted pressures including rising energy demand, environmental constraints, and the global drive toward renewable integration.

Digital transformation has led to the convergence of operational technologies and information technologies within the energy space. Robust machine learning models are now at the forefront, empowering organizations to forecast consumption patterns with higher accuracy, conduct real-time analysis of asset performance, and significantly reduce unplanned downtime. In this scenario, the emphasis on a proactive approach has shifted the focus from reactive solutions to already foreseeing and mitigating issues before they escalate.

The implementation of automated control systems and smart sensors has allowed companies to derive actionable insights from vast amounts of data. The integration of computer vision, natural language processing, and robotics has not only automated routine processes but also improved safety and operational efficiency. Moreover, the adoption of state-of-the-art AI technologies in decision-making processes has redefined operational benchmarks and set new standards for reliability and efficiency in energy distribution. Such transformational shifts are today influencing investment strategies, operational planning, and public policy, marking a critical inflection point in the industry's evolution.

Key Segmentation Insights for Market Growth

The segmentation of the market provides diverse lenses through which the impact of AI in the energy sector can be assessed. At the component level, the market is explored through the interplay of hardware, services, and software. Hardware solutions include advanced controllers, powerful processors, and intricate sensor arrays that facilitate data capture across the energy network. Service components encompass consulting services, deployment and integration expertise, and robust support and maintenance frameworks, ensuring systems run seamlessly. Software segments stretch across analytical solutions and comprehensive energy management software, underscoring the importance of data interpretation and agile control mechanisms in modern energy operations.

Further refinement in segmentation is achieved by examining technology types. This perspective highlights specialized applications such as computer vision, machine learning, natural language processing, and robotics. Within computer vision, the capability to perform image recognition and video analysis drives enhanced surveillance and asset tracking. The machine learning subdivision is elaborated into reinforcement learning, supervised learning, and unsupervised learning; these methodologies empower predictive analytics and adaptive system responses. Similarly, natural language processing spans language translation and sophisticated speech recognition, contributing to enhanced human-machine interfaces in control rooms.

A deeper insight emerges when the market is segmented by application areas. These include critical domains like demand-side management, energy management, grid management, and predictive maintenance. Within demand-side management, factors such as demand forecasting and energy efficiency optimization emerge as pivotal. Energy management becomes more nuanced through demand response, energy trading, and load forecasting strategies that enable operators to balance supply with fluctuating consumer demand. Grid management underscores the importance of grid monitoring and the development of microgrids, while predictive maintenance focuses on condition monitoring and proactive fault prediction to reduce downtime.

Finally, an analysis segmented by end users reveals demographically diverse demand patterns that influence market dynamics. Commercial establishments are examined through the lens of office buildings and shopping malls, while industrial applications delve into sectors such as mining and oil & gas. Residential applications focus on the rise of energy storage systems and smart home innovations that allow end users to manage consumption effectively. The utilities segment further dissects roles within the energy ecosystem by exploring distribution system operators and generation companies. This comprehensive segmentation helps in understanding the broad spectrum of AI applications and tailoring solutions to meet specific market needs effectively.

Based on Component, market is studied across Hardware, Services, and Software. The Hardware is further studied across Controllers, Processors, and Sensors. The Services is further studied across Consulting Services, Deployment & Integration, and Support & Maintenance. The Software is further studied across Analytical Solutions and Energy Management Software.

Based on Technology Types, market is studied across Computer Vision, Machine Learning, Natural Language Processing, and Robotics. The Computer Vision is further studied across Image Recognition and Video Analysis. The Machine Learning is further studied across Reinforcement Learning, Supervised Learning, and Unsupervised Learning. The Natural Language Processing is further studied across Language Translation and Speech Recognition.

Based on Application Areas, market is studied across Demand-Side Management, Energy Management, Grid Management, and Predictive Maintenance. The Demand-Side Management is further studied across Demand Forecasting and Energy Efficiency Optimization. The Energy Management is further studied across Demand Response, Energy Trading, and Load Forecasting. The Grid Management is further studied across Grid Monitoring and Microgrids. The Predictive Maintenance is further studied across Condition Monitoring and Fault Prediction.

Based on End User, market is studied across Commercial, Industrial, Residential, and Utilities. The Commercial is further studied across Office Buildings and Shopping Malls. The Industrial is further studied across Mining and Oil & Gas. The Residential is further studied across Energy Storage Systems and Smart Homes. The Utilities is further studied across Distribution System Operators and Generation Companies.

Key Regional Insights Across Global Markets

Regional dynamics are an essential element in understanding the deployment of AI within the energy sector. In the Americas, progressive policy frameworks and abundant investments in renewable technologies have spurred the adoption of avant-garde digital solutions. The characteristics of mature infrastructure and strong demand-side strategies enable energy firms in this region to lead in the implementation of AI-driven management systems. The region's emphasis on integrating smart grids and optimizing energy supply chains has catalyzed numerous innovations that serve as benchmarks for global practices.

In Europe, the Middle East, and Africa, the interplay between regulatory reforms and resource diversification plays a critical role in accelerating the digital transition. This region is characterized by an evolving market environment where public-private partnerships fuel advancement, and technology adoption is often backed by governmental incentives. The diversity within this region, spanning from advanced European hubs to rapidly growing energy markets in the Middle East and Africa, marks a unique blend of legacy infrastructure and cutting-edge research in AI-enabled energy solutions.

The Asia-Pacific region stands out due to its rapid industrial expansion and significant investments in sustainable development. Here, energy consumption patterns are evolving quickly as urbanization and technological advancement drive demand for more efficient management systems. Integrated AI solutions are quickly being adopted to handle the massive influx of data generated from smart city projects and renewable integrations. The combination of cost-effective technology deployment and the drive for modernization makes the Asia-Pacific a significant contributor to innovation in the energy sector.

Based on Region, market is studied across Americas, Asia-Pacific, and Europe, Middle East & Africa. The Americas is further studied across Argentina, Brazil, Canada, Mexico, and United States. The United States is further studied across California, Florida, Illinois, New York, Ohio, Pennsylvania, and Texas. The Asia-Pacific is further studied across Australia, China, India, Indonesia, Japan, Malaysia, Philippines, Singapore, South Korea, Taiwan, Thailand, and Vietnam. The Europe, Middle East & Africa is further studied across Denmark, Egypt, Finland, France, Germany, Israel, Italy, Netherlands, Nigeria, Norway, Poland, Qatar, Russia, Saudi Arabia, South Africa, Spain, Sweden, Switzerland, Turkey, United Arab Emirates, and United Kingdom.

Key Companies Influencing the AI in Energy Landscape

Several industry players have emerged at the intersection of artificial intelligence and energy. Leaders such as ABB Ltd. and C3.ai, Inc. have been instrumental in integrating AI-driven solutions with traditional energy systems, thereby enabling significant improvements across operational pipelines and strategic planning. Eaton Corporation and ENEL Group have utilized intelligent automation to balance production efficiencies, while Engie SA and General Electric Company continue to innovate in the realm of predictive maintenance and grid management.

Giants like Google, LLC and IBM Corporation have contributed extensive technological expertise, integrating machine learning and cloud computing to enhance data processing capabilities. Grid4C and Honeywell International Inc. provide specialized services that focus on energy conservation and real-time analytics, while Microsoft Corporation and Mitsubishi Electric Corporation continually push the envelope on software-driven automation in power generation. NextEra Energy, Inc. and Nokia Corporation have positioned themselves as pioneers in employing smart technologies to balance regional power grids, and renowned enterprises such as Saudi Arabian Oil Co. and Schneider Electric are increasingly leveraging AI for greater operational efficiencies.

Furthermore, Siemens AG, Uplight, Inc., Uptake Technologies, Inc., and Verdigris Technologies continue to lead the charge by offering novel solutions that combine advanced robotics, sensor technology, and real-time analytics. Their combined efforts in driving AI adoption underscore the transformative potential of digital solutions in energy management, paving the way for smarter, more resilient infrastructure on a global scale.

The report delves into recent significant developments in the Artificial Intelligence in Energy Market, highlighting leading vendors and their innovative profiles. These include ABB Ltd., C3.ai, Inc., Eaton Corporation, ENEL Group, Engie SA, General Electric Company, Google, LLC, Grid4C, Honeywell International Inc., IBM Corporation, Microsoft Corporation, Mitsubishi Electric Corporation, NextEra Energy, Inc., Nokia Corporation, Saudi Arabian Oil Co., Schneider Electric, Siemens AG, Uplight, Inc., Uptake Technologies, Inc., and Verdigris Technologies. Actionable Recommendations for Industry Leaders to Embrace AI

Industry leaders must prioritize the integration of artificial intelligence to transform traditional energy operations into agile, data-driven networks. First, enhance operational visibility by investing in robust hardware solutions and sophisticated sensor technologies that provide real-time insights into energy flows. Implementation of advanced controller systems can optimize grid performance and minimize energy losses.

Leaders should also focus on building comprehensive ecosystems that blend hardware, services, and software. It is critical to deploy consulting services that aid in system integration, ensuring that new digital technologies are seamlessly merged with legacy systems while enhancing overall efficiency. Recognizing the value of analytical solutions and energy management software is also fundamental in deriving actionable insights that drive strategic decision-making.

Further, organizations must leverage the latest innovations in machine learning, computer vision, natural language processing, and robotics to gain a competitive edge. Adopting these technologies can lead to more accurate demand forecasting, improved grid monitoring, and enhanced predictive maintenance strategies. With the rapid evolution of digital tools, it is essential to foster a culture of continuous learning and technological agility within the organization.

Finally, industry leaders should evaluate regional market dynamics and the strengths of diverse AI technology providers to tailor localized solutions. Collaborating with technology innovators and consulting with research professionals will help identify the most effective strategies for digital transformation. These proactive measures not only lay the groundwork for sustainable growth but also facilitate a smoother transition towards a fully integrated, AI-powered energy ecosystem.

Conclusion: Embracing the Future of AI in Energy

The evolution of artificial intelligence in the energy sector represents a seismic shift towards efficiency, sustainability, and innovation. This transformation, driven by advanced digital solutions, has redefined operational paradigms and opened new avenues for energy management. By analyzing segmentation across components, technology types, application areas, and end users, the evolving narrative in the energy industry becomes evident. Regional perspectives further underscore the variety of challenges and opportunities faced across different markets, while leading companies showcase a commitment to delivering groundbreaking solutions. Ultimately, the path forward is clear for organizations that embrace these innovations, guiding the sector toward a smarter and more resilient future.

Table of Contents

1. Preface

  • 1.1. Objectives of the Study
  • 1.2. Market Segmentation & Coverage
  • 1.3. Years Considered for the Study
  • 1.4. Currency & Pricing
  • 1.5. Language
  • 1.6. Stakeholders

2. Research Methodology

  • 2.1. Define: Research Objective
  • 2.2. Determine: Research Design
  • 2.3. Prepare: Research Instrument
  • 2.4. Collect: Data Source
  • 2.5. Analyze: Data Interpretation
  • 2.6. Formulate: Data Verification
  • 2.7. Publish: Research Report
  • 2.8. Repeat: Report Update

3. Executive Summary

4. Market Overview

5. Market Insights

  • 5.1. Market Dynamics
    • 5.1.1. Drivers
      • 5.1.1.1. Growing adoption of AI-enabled smart grid technologies to enhance energy efficiency and sustainability goals
      • 5.1.1.2. Rising demand for AI-driven predictive maintenance solutions to reduce operational costs in energy infrastructure
    • 5.1.2. Restraints
      • 5.1.2.1. High implementation costs and complex integration processes limiting ai adoption in energy systems
    • 5.1.3. Opportunities
      • 5.1.3.1. Development of AI-powered energy storage solutions to address intermittency in renewable energy sources
      • 5.1.3.2. Increasing deployment of AI in renewable energy management to optimize resource utilization and grid stability
    • 5.1.4. Challenges
      • 5.1.4.1. Data privacy concerns and regulatory uncertainty affecting the scalability of AI in energy applications
  • 5.2. Market Segmentation Analysis
    • 5.2.1. Component: Hardware components driving artificial intelligence in energy systems
    • 5.2.2. End User: Artificial intelligence applications in the industrial sector for energy optimization
  • 5.3. Porter's Five Forces Analysis
    • 5.3.1. Threat of New Entrants
    • 5.3.2. Threat of Substitutes
    • 5.3.3. Bargaining Power of Customers
    • 5.3.4. Bargaining Power of Suppliers
    • 5.3.5. Industry Rivalry
  • 5.4. PESTLE Analysis
    • 5.4.1. Political
    • 5.4.2. Economic
    • 5.4.3. Social
    • 5.4.4. Technological
    • 5.4.5. Legal
    • 5.4.6. Environmental

6. Artificial Intelligence in Energy Market, by Component

  • 6.1. Introduction
  • 6.2. Hardware
    • 6.2.1. Controllers
    • 6.2.2. Processors
    • 6.2.3. Sensors
  • 6.3. Services
    • 6.3.1. Consulting Services
    • 6.3.2. Deployment & Integration
    • 6.3.3. Support & Maintenance
  • 6.4. Software
    • 6.4.1. Analytical Solutions
    • 6.4.2. Energy Management Software

7. Artificial Intelligence in Energy Market, by Technology Types

  • 7.1. Introduction
  • 7.2. Computer Vision
    • 7.2.1. Image Recognition
    • 7.2.2. Video Analysis
  • 7.3. Machine Learning
    • 7.3.1. Reinforcement Learning
    • 7.3.2. Supervised Learning
    • 7.3.3. Unsupervised Learning
  • 7.4. Natural Language Processing
    • 7.4.1. Language Translation
    • 7.4.2. Speech Recognition
  • 7.5. Robotics

8. Artificial Intelligence in Energy Market, by Application Areas

  • 8.1. Introduction
  • 8.2. Demand-Side Management
    • 8.2.1. Demand Forecasting
    • 8.2.2. Energy Efficiency Optimization
  • 8.3. Energy Management
    • 8.3.1. Demand Response
    • 8.3.2. Energy Trading
    • 8.3.3. Load Forecasting
  • 8.4. Grid Management
    • 8.4.1. Grid Monitoring
    • 8.4.2. Microgrids
  • 8.5. Predictive Maintenance
    • 8.5.1. Condition Monitoring
    • 8.5.2. Fault Prediction

9. Artificial Intelligence in Energy Market, by End User

  • 9.1. Introduction
  • 9.2. Commercial
    • 9.2.1. Office Buildings
    • 9.2.2. Shopping Malls
  • 9.3. Industrial
    • 9.3.1. Mining
    • 9.3.2. Oil & Gas
  • 9.4. Residential
    • 9.4.1. Energy Storage Systems
    • 9.4.2. Smart Homes
  • 9.5. Utilities
    • 9.5.1. Distribution System Operators
    • 9.5.2. Generation Companies

10. Americas Artificial Intelligence in Energy Market

  • 10.1. Introduction
  • 10.2. Argentina
  • 10.3. Brazil
  • 10.4. Canada
  • 10.5. Mexico
  • 10.6. United States

11. Asia-Pacific Artificial Intelligence in Energy Market

  • 11.1. Introduction
  • 11.2. Australia
  • 11.3. China
  • 11.4. India
  • 11.5. Indonesia
  • 11.6. Japan
  • 11.7. Malaysia
  • 11.8. Philippines
  • 11.9. Singapore
  • 11.10. South Korea
  • 11.11. Taiwan
  • 11.12. Thailand
  • 11.13. Vietnam

12. Europe, Middle East & Africa Artificial Intelligence in Energy Market

  • 12.1. Introduction
  • 12.2. Denmark
  • 12.3. Egypt
  • 12.4. Finland
  • 12.5. France
  • 12.6. Germany
  • 12.7. Israel
  • 12.8. Italy
  • 12.9. Netherlands
  • 12.10. Nigeria
  • 12.11. Norway
  • 12.12. Poland
  • 12.13. Qatar
  • 12.14. Russia
  • 12.15. Saudi Arabia
  • 12.16. South Africa
  • 12.17. Spain
  • 12.18. Sweden
  • 12.19. Switzerland
  • 12.20. Turkey
  • 12.21. United Arab Emirates
  • 12.22. United Kingdom

13. Competitive Landscape

  • 13.1. Market Share Analysis, 2024
  • 13.2. FPNV Positioning Matrix, 2024
  • 13.3. Competitive Scenario Analysis
    • 13.3.1. Hitachi Energy's Nostradamus AI transforms energy forecasting and operational efficiency
    • 13.3.2. Honeywell to power energy sector with new artificial intelligence solutions
    • 13.3.3. BlackRock and Microsoft lead USD 100 billion partnership to transform AI infrastructure and energy sectors
  • 13.4. Strategy Analysis & Recommendation

Companies Mentioned

  • 1. ABB Ltd.
  • 2. C3.ai, Inc.
  • 3. Eaton Corporation
  • 4. ENEL Group
  • 5. Engie SA
  • 6. General Electric Company
  • 7. Google, LLC
  • 8. Grid4C
  • 9. Honeywell International Inc.
  • 10. IBM Corporation
  • 11. Microsoft Corporation
  • 12. Mitsubishi Electric Corporation
  • 13. NextEra Energy, Inc.
  • 14. Nokia Corporation
  • 15. Saudi Arabian Oil Co.
  • 16. Schneider Electric
  • 17. Siemens AG
  • 18. Uplight, Inc.
  • 19. Uptake Technologies, Inc.
  • 20. Verdigris Technologies

LIST OF FIGURES

  • FIGURE 1. ARTIFICIAL INTELLIGENCE IN ENERGY MARKET MULTI-CURRENCY
  • FIGURE 2. ARTIFICIAL INTELLIGENCE IN ENERGY MARKET MULTI-LANGUAGE
  • FIGURE 3. ARTIFICIAL INTELLIGENCE IN ENERGY MARKET RESEARCH PROCESS
  • FIGURE 4. ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, 2024 VS 2030
  • FIGURE 5. GLOBAL ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, 2018-2030 (USD MILLION)
  • FIGURE 6. GLOBAL ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY REGION, 2024 VS 2025 VS 2030 (USD MILLION)
  • FIGURE 7. GLOBAL ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY COUNTRY, 2024 VS 2025 VS 2030 (USD MILLION)
  • FIGURE 8. GLOBAL ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY COMPONENT, 2024 VS 2030 (%)
  • FIGURE 9. GLOBAL ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY COMPONENT, 2024 VS 2025 VS 2030 (USD MILLION)
  • FIGURE 10. GLOBAL ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY TECHNOLOGY TYPES, 2024 VS 2030 (%)
  • FIGURE 11. GLOBAL ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY TECHNOLOGY TYPES, 2024 VS 2025 VS 2030 (USD MILLION)
  • FIGURE 12. GLOBAL ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY APPLICATION AREAS, 2024 VS 2030 (%)
  • FIGURE 13. GLOBAL ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY APPLICATION AREAS, 2024 VS 2025 VS 2030 (USD MILLION)
  • FIGURE 14. GLOBAL ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY END USER, 2024 VS 2030 (%)
  • FIGURE 15. GLOBAL ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY END USER, 2024 VS 2025 VS 2030 (USD MILLION)
  • FIGURE 16. AMERICAS ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY COUNTRY, 2024 VS 2030 (%)
  • FIGURE 17. AMERICAS ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY COUNTRY, 2024 VS 2025 VS 2030 (USD MILLION)
  • FIGURE 18. UNITED STATES ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY STATE, 2024 VS 2030 (%)
  • FIGURE 19. UNITED STATES ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY STATE, 2024 VS 2025 VS 2030 (USD MILLION)
  • FIGURE 20. ASIA-PACIFIC ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY COUNTRY, 2024 VS 2030 (%)
  • FIGURE 21. ASIA-PACIFIC ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY COUNTRY, 2024 VS 2025 VS 2030 (USD MILLION)
  • FIGURE 22. EUROPE, MIDDLE EAST & AFRICA ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY COUNTRY, 2024 VS 2030 (%)
  • FIGURE 23. EUROPE, MIDDLE EAST & AFRICA ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY COUNTRY, 2024 VS 2025 VS 2030 (USD MILLION)
  • FIGURE 24. ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SHARE, BY KEY PLAYER, 2024
  • FIGURE 25. ARTIFICIAL INTELLIGENCE IN ENERGY MARKET, FPNV POSITIONING MATRIX, 2024

LIST OF TABLES

  • TABLE 1. ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SEGMENTATION & COVERAGE
  • TABLE 2. UNITED STATES DOLLAR EXCHANGE RATE, 2018-2024
  • TABLE 3. GLOBAL ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, 2018-2030 (USD MILLION)
  • TABLE 4. GLOBAL ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY REGION, 2018-2030 (USD MILLION)
  • TABLE 5. GLOBAL ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY COUNTRY, 2018-2030 (USD MILLION)
  • TABLE 6. ARTIFICIAL INTELLIGENCE IN ENERGY MARKET DYNAMICS
  • TABLE 7. GLOBAL ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY COMPONENT, 2018-2030 (USD MILLION)
  • TABLE 8. GLOBAL ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY HARDWARE, BY REGION, 2018-2030 (USD MILLION)
  • TABLE 9. GLOBAL ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY CONTROLLERS, BY REGION, 2018-2030 (USD MILLION)
  • TABLE 10. GLOBAL ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY PROCESSORS, BY REGION, 2018-2030 (USD MILLION)
  • TABLE 11. GLOBAL ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY SENSORS, BY REGION, 2018-2030 (USD MILLION)
  • TABLE 12. GLOBAL ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY HARDWARE, 2018-2030 (USD MILLION)
  • TABLE 13. GLOBAL ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY SERVICES, BY REGION, 2018-2030 (USD MILLION)
  • TABLE 14. GLOBAL ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY CONSULTING SERVICES, BY REGION, 2018-2030 (USD MILLION)
  • TABLE 15. GLOBAL ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY DEPLOYMENT & INTEGRATION, BY REGION, 2018-2030 (USD MILLION)
  • TABLE 16. GLOBAL ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY SUPPORT & MAINTENANCE, BY REGION, 2018-2030 (USD MILLION)
  • TABLE 17. GLOBAL ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY SERVICES, 2018-2030 (USD MILLION)
  • TABLE 18. GLOBAL ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY SOFTWARE, BY REGION, 2018-2030 (USD MILLION)
  • TABLE 19. GLOBAL ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY ANALYTICAL SOLUTIONS, BY REGION, 2018-2030 (USD MILLION)
  • TABLE 20. GLOBAL ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY ENERGY MANAGEMENT SOFTWARE, BY REGION, 2018-2030 (USD MILLION)
  • TABLE 21. GLOBAL ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY SOFTWARE, 2018-2030 (USD MILLION)
  • TABLE 22. GLOBAL ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY TECHNOLOGY TYPES, 2018-2030 (USD MILLION)
  • TABLE 23. GLOBAL ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY COMPUTER VISION, BY REGION, 2018-2030 (USD MILLION)
  • TABLE 24. GLOBAL ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY IMAGE RECOGNITION, BY REGION, 2018-2030 (USD MILLION)
  • TABLE 25. GLOBAL ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY VIDEO ANALYSIS, BY REGION, 2018-2030 (USD MILLION)
  • TABLE 26. GLOBAL ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY COMPUTER VISION, 2018-2030 (USD MILLION)
  • TABLE 27. GLOBAL ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY MACHINE LEARNING, BY REGION, 2018-2030 (USD MILLION)
  • TABLE 28. GLOBAL ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY REINFORCEMENT LEARNING, BY REGION, 2018-2030 (USD MILLION)
  • TABLE 29. GLOBAL ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY SUPERVISED LEARNING, BY REGION, 2018-2030 (USD MILLION)
  • TABLE 30. GLOBAL ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY UNSUPERVISED LEARNING, BY REGION, 2018-2030 (USD MILLION)
  • TABLE 31. GLOBAL ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY MACHINE LEARNING, 2018-2030 (USD MILLION)
  • TABLE 32. GLOBAL ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY NATURAL LANGUAGE PROCESSING, BY REGION, 2018-2030 (USD MILLION)
  • TABLE 33. GLOBAL ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY LANGUAGE TRANSLATION, BY REGION, 2018-2030 (USD MILLION)
  • TABLE 34. GLOBAL ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY SPEECH RECOGNITION, BY REGION, 2018-2030 (USD MILLION)
  • TABLE 35. GLOBAL ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY NATURAL LANGUAGE PROCESSING, 2018-2030 (USD MILLION)
  • TABLE 36. GLOBAL ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY ROBOTICS, BY REGION, 2018-2030 (USD MILLION)
  • TABLE 37. GLOBAL ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY APPLICATION AREAS, 2018-2030 (USD MILLION)
  • TABLE 38. GLOBAL ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY DEMAND-SIDE MANAGEMENT, BY REGION, 2018-2030 (USD MILLION)
  • TABLE 39. GLOBAL ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY DEMAND FORECASTING, BY REGION, 2018-2030 (USD MILLION)
  • TABLE 40. GLOBAL ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY ENERGY EFFICIENCY OPTIMIZATION, BY REGION, 2018-2030 (USD MILLION)
  • TABLE 41. GLOBAL ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY DEMAND-SIDE MANAGEMENT, 2018-2030 (USD MILLION)
  • TABLE 42. GLOBAL ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY ENERGY MANAGEMENT, BY REGION, 2018-2030 (USD MILLION)
  • TABLE 43. GLOBAL ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY DEMAND RESPONSE, BY REGION, 2018-2030 (USD MILLION)
  • TABLE 44. GLOBAL ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY ENERGY TRADING, BY REGION, 2018-2030 (USD MILLION)
  • TABLE 45. GLOBAL ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY LOAD FORECASTING, BY REGION, 2018-2030 (USD MILLION)
  • TABLE 46. GLOBAL ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY ENERGY MANAGEMENT, 2018-2030 (USD MILLION)
  • TABLE 47. GLOBAL ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY GRID MANAGEMENT, BY REGION, 2018-2030 (USD MILLION)
  • TABLE 48. GLOBAL ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY GRID MONITORING, BY REGION, 2018-2030 (USD MILLION)
  • TABLE 49. GLOBAL ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY MICROGRIDS, BY REGION, 2018-2030 (USD MILLION)
  • TABLE 50. GLOBAL ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY GRID MANAGEMENT, 2018-2030 (USD MILLION)
  • TABLE 51. GLOBAL ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY PREDICTIVE MAINTENANCE, BY REGION, 2018-2030 (USD MILLION)
  • TABLE 52. GLOBAL ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY CONDITION MONITORING, BY REGION, 2018-2030 (USD MILLION)
  • TABLE 53. GLOBAL ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY FAULT PREDICTION, BY REGION, 2018-2030 (USD MILLION)
  • TABLE 54. GLOBAL ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY PREDICTIVE MAINTENANCE, 2018-2030 (USD MILLION)
  • TABLE 55. GLOBAL ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY END USER, 2018-2030 (USD MILLION)
  • TABLE 56. GLOBAL ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY COMMERCIAL, BY REGION, 2018-2030 (USD MILLION)
  • TABLE 57. GLOBAL ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY OFFICE BUILDINGS, BY REGION, 2018-2030 (USD MILLION)
  • TABLE 58. GLOBAL ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY SHOPPING MALLS, BY REGION, 2018-2030 (USD MILLION)
  • TABLE 59. GLOBAL ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY COMMERCIAL, 2018-2030 (USD MILLION)
  • TABLE 60. GLOBAL ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY INDUSTRIAL, BY REGION, 2018-2030 (USD MILLION)
  • TABLE 61. GLOBAL ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY MINING, BY REGION, 2018-2030 (USD MILLION)
  • TABLE 62. GLOBAL ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY OIL & GAS, BY REGION, 2018-2030 (USD MILLION)
  • TABLE 63. GLOBAL ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY INDUSTRIAL, 2018-2030 (USD MILLION)
  • TABLE 64. GLOBAL ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY RESIDENTIAL, BY REGION, 2018-2030 (USD MILLION)
  • TABLE 65. GLOBAL ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY ENERGY STORAGE SYSTEMS, BY REGION, 2018-2030 (USD MILLION)
  • TABLE 66. GLOBAL ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY SMART HOMES, BY REGION, 2018-2030 (USD MILLION)
  • TABLE 67. GLOBAL ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY RESIDENTIAL, 2018-2030 (USD MILLION)
  • TABLE 68. GLOBAL ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY UTILITIES, BY REGION, 2018-2030 (USD MILLION)
  • TABLE 69. GLOBAL ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY DISTRIBUTION SYSTEM OPERATORS, BY REGION, 2018-2030 (USD MILLION)
  • TABLE 70. GLOBAL ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY GENERATION COMPANIES, BY REGION, 2018-2030 (USD MILLION)
  • TABLE 71. GLOBAL ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY UTILITIES, 2018-2030 (USD MILLION)
  • TABLE 72. AMERICAS ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY COMPONENT, 2018-2030 (USD MILLION)
  • TABLE 73. AMERICAS ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY HARDWARE, 2018-2030 (USD MILLION)
  • TABLE 74. AMERICAS ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY SERVICES, 2018-2030 (USD MILLION)
  • TABLE 75. AMERICAS ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY SOFTWARE, 2018-2030 (USD MILLION)
  • TABLE 76. AMERICAS ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY TECHNOLOGY TYPES, 2018-2030 (USD MILLION)
  • TABLE 77. AMERICAS ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY COMPUTER VISION, 2018-2030 (USD MILLION)
  • TABLE 78. AMERICAS ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY MACHINE LEARNING, 2018-2030 (USD MILLION)
  • TABLE 79. AMERICAS ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY NATURAL LANGUAGE PROCESSING, 2018-2030 (USD MILLION)
  • TABLE 80. AMERICAS ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY APPLICATION AREAS, 2018-2030 (USD MILLION)
  • TABLE 81. AMERICAS ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY DEMAND-SIDE MANAGEMENT, 2018-2030 (USD MILLION)
  • TABLE 82. AMERICAS ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY ENERGY MANAGEMENT, 2018-2030 (USD MILLION)
  • TABLE 83. AMERICAS ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY GRID MANAGEMENT, 2018-2030 (USD MILLION)
  • TABLE 84. AMERICAS ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY PREDICTIVE MAINTENANCE, 2018-2030 (USD MILLION)
  • TABLE 85. AMERICAS ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY END USER, 2018-2030 (USD MILLION)
  • TABLE 86. AMERICAS ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY COMMERCIAL, 2018-2030 (USD MILLION)
  • TABLE 87. AMERICAS ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY INDUSTRIAL, 2018-2030 (USD MILLION)
  • TABLE 88. AMERICAS ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY RESIDENTIAL, 2018-2030 (USD MILLION)
  • TABLE 89. AMERICAS ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY UTILITIES, 2018-2030 (USD MILLION)
  • TABLE 90. AMERICAS ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY COUNTRY, 2018-2030 (USD MILLION)
  • TABLE 91. ARGENTINA ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY COMPONENT, 2018-2030 (USD MILLION)
  • TABLE 92. ARGENTINA ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY HARDWARE, 2018-2030 (USD MILLION)
  • TABLE 93. ARGENTINA ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY SERVICES, 2018-2030 (USD MILLION)
  • TABLE 94. ARGENTINA ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY SOFTWARE, 2018-2030 (USD MILLION)
  • TABLE 95. ARGENTINA ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY TECHNOLOGY TYPES, 2018-2030 (USD MILLION)
  • TABLE 96. ARGENTINA ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY COMPUTER VISION, 2018-2030 (USD MILLION)
  • TABLE 97. ARGENTINA ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY MACHINE LEARNING, 2018-2030 (USD MILLION)
  • TABLE 98. ARGENTINA ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY NATURAL LANGUAGE PROCESSING, 2018-2030 (USD MILLION)
  • TABLE 99. ARGENTINA ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY APPLICATION AREAS, 2018-2030 (USD MILLION)
  • TABLE 100. ARGENTINA ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY DEMAND-SIDE MANAGEMENT, 2018-2030 (USD MILLION)
  • TABLE 101. ARGENTINA ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY ENERGY MANAGEMENT, 2018-2030 (USD MILLION)
  • TABLE 102. ARGENTINA ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY GRID MANAGEMENT, 2018-2030 (USD MILLION)
  • TABLE 103. ARGENTINA ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY PREDICTIVE MAINTENANCE, 2018-2030 (USD MILLION)
  • TABLE 104. ARGENTINA ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY END USER, 2018-2030 (USD MILLION)
  • TABLE 105. ARGENTINA ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY COMMERCIAL, 2018-2030 (USD MILLION)
  • TABLE 106. ARGENTINA ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY INDUSTRIAL, 2018-2030 (USD MILLION)
  • TABLE 107. ARGENTINA ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY RESIDENTIAL, 2018-2030 (USD MILLION)
  • TABLE 108. ARGENTINA ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY UTILITIES, 2018-2030 (USD MILLION)
  • TABLE 109. BRAZIL ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY COMPONENT, 2018-2030 (USD MILLION)
  • TABLE 110. BRAZIL ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY HARDWARE, 2018-2030 (USD MILLION)
  • TABLE 111. BRAZIL ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY SERVICES, 2018-2030 (USD MILLION)
  • TABLE 112. BRAZIL ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY SOFTWARE, 2018-2030 (USD MILLION)
  • TABLE 113. BRAZIL ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY TECHNOLOGY TYPES, 2018-2030 (USD MILLION)
  • TABLE 114. BRAZIL ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY COMPUTER VISION, 2018-2030 (USD MILLION)
  • TABLE 115. BRAZIL ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY MACHINE LEARNING, 2018-2030 (USD MILLION)
  • TABLE 116. BRAZIL ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY NATURAL LANGUAGE PROCESSING, 2018-2030 (USD MILLION)
  • TABLE 117. BRAZIL ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY APPLICATION AREAS, 2018-2030 (USD MILLION)
  • TABLE 118. BRAZIL ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY DEMAND-SIDE MANAGEMENT, 2018-2030 (USD MILLION)
  • TABLE 119. BRAZIL ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY ENERGY MANAGEMENT, 2018-2030 (USD MILLION)
  • TABLE 120. BRAZIL ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY GRID MANAGEMENT, 2018-2030 (USD MILLION)
  • TABLE 121. BRAZIL ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY PREDICTIVE MAINTENANCE, 2018-2030 (USD MILLION)
  • TABLE 122. BRAZIL ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY END USER, 2018-2030 (USD MILLION)
  • TABLE 123. BRAZIL ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY COMMERCIAL, 2018-2030 (USD MILLION)
  • TABLE 124. BRAZIL ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY INDUSTRIAL, 2018-2030 (USD MILLION)
  • TABLE 125. BRAZIL ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY RESIDENTIAL, 2018-2030 (USD MILLION)
  • TABLE 126. BRAZIL ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY UTILITIES, 2018-2030 (USD MILLION)
  • TABLE 127. CANADA ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY COMPONENT, 2018-2030 (USD MILLION)
  • TABLE 128. CANADA ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY HARDWARE, 2018-2030 (USD MILLION)
  • TABLE 129. CANADA ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY SERVICES, 2018-2030 (USD MILLION)
  • TABLE 130. CANADA ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY SOFTWARE, 2018-2030 (USD MILLION)
  • TABLE 131. CANADA ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY TECHNOLOGY TYPES, 2018-2030 (USD MILLION)
  • TABLE 132. CANADA ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY COMPUTER VISION, 2018-2030 (USD MILLION)
  • TABLE 133. CANADA ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY MACHINE LEARNING, 2018-2030 (USD MILLION)
  • TABLE 134. CANADA ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY NATURAL LANGUAGE PROCESSING, 2018-2030 (USD MILLION)
  • TABLE 135. CANADA ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY APPLICATION AREAS, 2018-2030 (USD MILLION)
  • TABLE 136. CANADA ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY DEMAND-SIDE MANAGEMENT, 2018-2030 (USD MILLION)
  • TABLE 137. CANADA ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY ENERGY MANAGEMENT, 2018-2030 (USD MILLION)
  • TABLE 138. CANADA ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY GRID MANAGEMENT, 2018-2030 (USD MILLION)
  • TABLE 139. CANADA ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY PREDICTIVE MAINTENANCE, 2018-2030 (USD MILLION)
  • TABLE 140. CANADA ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY END USER, 2018-2030 (USD MILLION)
  • TABLE 141. CANADA ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY COMMERCIAL, 2018-2030 (USD MILLION)
  • TABLE 142. CANADA ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY INDUSTRIAL, 2018-2030 (USD MILLION)
  • TABLE 143. CANADA ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY RESIDENTIAL, 2018-2030 (USD MILLION)
  • TABLE 144. CANADA ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY UTILITIES, 2018-2030 (USD MILLION)
  • TABLE 145. MEXICO ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY COMPONENT, 2018-2030 (USD MILLION)
  • TABLE 146. MEXICO ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY HARDWARE, 2018-2030 (USD MILLION)
  • TABLE 147. MEXICO ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY SERVICES, 2018-2030 (USD MILLION)
  • TABLE 148. MEXICO ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY SOFTWARE, 2018-2030 (USD MILLION)
  • TABLE 149. MEXICO ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY TECHNOLOGY TYPES, 2018-2030 (USD MILLION)
  • TABLE 150. MEXICO ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY COMPUTER VISION, 2018-2030 (USD MILLION)
  • TABLE 151. MEXICO ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY MACHINE LEARNING, 2018-2030 (USD MILLION)
  • TABLE 152. MEXICO ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY NATURAL LANGUAGE PROCESSING, 2018-2030 (USD MILLION)
  • TABLE 153. MEXICO ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY APPLICATION AREAS, 2018-2030 (USD MILLION)
  • TABLE 154. MEXICO ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY DEMAND-SIDE MANAGEMENT, 2018-2030 (USD MILLION)
  • TABLE 155. MEXICO ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY ENERGY MANAGEMENT, 2018-2030 (USD MILLION)
  • TABLE 156. MEXICO ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY GRID MANAGEMENT, 2018-2030 (USD MILLION)
  • TABLE 157. MEXICO ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY PREDICTIVE MAINTENANCE, 2018-2030 (USD MILLION)
  • TABLE 158. MEXICO ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY END USER, 2018-2030 (USD MILLION)
  • TABLE 159. MEXICO ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY COMMERCIAL, 2018-2030 (USD MILLION)
  • TABLE 160. MEXICO ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY INDUSTRIAL, 2018-2030 (USD MILLION)
  • TABLE 161. MEXICO ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY RESIDENTIAL, 2018-2030 (USD MILLION)
  • TABLE 162. MEXICO ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY UTILITIES, 2018-2030 (USD MILLION)
  • TABLE 163. UNITED STATES ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY COMPONENT, 2018-2030 (USD MILLION)
  • TABLE 164. UNITED STATES ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY HARDWARE, 2018-2030 (USD MILLION)
  • TABLE 165. UNITED STATES ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY SERVICES, 2018-2030 (USD MILLION)
  • TABLE 166. UNITED STATES ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY SOFTWARE, 2018-2030 (USD MILLION)
  • TABLE 167. UNITED STATES ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY TECHNOLOGY TYPES, 2018-2030 (USD MILLION)
  • TABLE 168. UNITED STATES ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY COMPUTER VISION, 2018-2030 (USD MILLION)
  • TABLE 169. UNITED STATES ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY MACHINE LEARNING, 2018-2030 (USD MILLION)
  • TABLE 170. UNITED STATES ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY NATURAL LANGUAGE PROCESSING, 2018-2030 (USD MILLION)
  • TABLE 171. UNITED STATES ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY APPLICATION AREAS, 2018-2030 (USD MILLION)
  • TABLE 172. UNITED STATES ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY DEMAND-SIDE MANAGEMENT, 2018-2030 (USD MILLION)
  • TABLE 173. UNITED STATES ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY ENERGY MANAGEMENT, 2018-2030 (USD MILLION)
  • TABLE 174. UNITED STATES ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY GRID MANAGEMENT, 2018-2030 (USD MILLION)
  • TABLE 175. UNITED STATES ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY PREDICTIVE MAINTENANCE, 2018-2030 (USD MILLION)
  • TABLE 176. UNITED STATES ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY END USER, 2018-2030 (USD MILLION)
  • TABLE 177. UNITED STATES ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY COMMERCIAL, 2018-2030 (USD MILLION)
  • TABLE 178. UNITED STATES ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY INDUSTRIAL, 2018-2030 (USD MILLION)
  • TABLE 179. UNITED STATES ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY RESIDENTIAL, 2018-2030 (USD MILLION)
  • TABLE 180. UNITED STATES ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY UTILITIES, 2018-2030 (USD MILLION)
  • TABLE 181. UNITED STATES ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY STATE, 2018-2030 (USD MILLION)
  • TABLE 182. ASIA-PACIFIC ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY COMPONENT, 2018-2030 (USD MILLION)
  • TABLE 183. ASIA-PACIFIC ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY HARDWARE, 2018-2030 (USD MILLION)
  • TABLE 184. ASIA-PACIFIC ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY SERVICES, 2018-2030 (USD MILLION)
  • TABLE 185. ASIA-PACIFIC ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY SOFTWARE, 2018-2030 (USD MILLION)
  • TABLE 186. ASIA-PACIFIC ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY TECHNOLOGY TYPES, 2018-2030 (USD MILLION)
  • TABLE 187. ASIA-PACIFIC ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY COMPUTER VISION, 2018-2030 (USD MILLION)
  • TABLE 188. ASIA-PACIFIC ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY MACHINE LEARNING, 2018-2030 (USD MILLION)
  • TABLE 189. ASIA-PACIFIC ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY NATURAL LANGUAGE PROCESSING, 2018-2030 (USD MILLION)
  • TABLE 190. ASIA-PACIFIC ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY APPLICATION AREAS, 2018-2030 (USD MILLION)
  • TABLE 191. ASIA-PACIFIC ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY DEMAND-SIDE MANAGEMENT, 2018-2030 (USD MILLION)
  • TABLE 192. ASIA-PACIFIC ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY ENERGY MANAGEMENT, 2018-2030 (USD MILLION)
  • TABLE 193. ASIA-PACIFIC ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY GRID MANAGEMENT, 2018-2030 (USD MILLION)
  • TABLE 194. ASIA-PACIFIC ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY PREDICTIVE MAINTENANCE, 2018-2030 (USD MILLION)
  • TABLE 195. ASIA-PACIFIC ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY END USER, 2018-2030 (USD MILLION)
  • TABLE 196. ASIA-PACIFIC ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY COMMERCIAL, 2018-2030 (USD MILLION)
  • TABLE 197. ASIA-PACIFIC ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY INDUSTRIAL, 2018-2030 (USD MILLION)
  • TABLE 198. ASIA-PACIFIC ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY RESIDENTIAL, 2018-2030 (USD MILLION)
  • TABLE 199. ASIA-PACIFIC ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY UTILITIES, 2018-2030 (USD MILLION)
  • TABLE 200. ASIA-PACIFIC ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY COUNTRY, 2018-2030 (USD MILLION)
  • TABLE 201. AUSTRALIA ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY COMPONENT, 2018-2030 (USD MILLION)
  • TABLE 202. AUSTRALIA ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY HARDWARE, 2018-2030 (USD MILLION)
  • TABLE 203. AUSTRALIA ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY SERVICES, 2018-2030 (USD MILLION)
  • TABLE 204. AUSTRALIA ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY SOFTWARE, 2018-2030 (USD MILLION)
  • TABLE 205. AUSTRALIA ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY TECHNOLOGY TYPES, 2018-2030 (USD MILLION)
  • TABLE 206. AUSTRALIA ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY COMPUTER VISION, 2018-2030 (USD MILLION)
  • TABLE 207. AUSTRALIA ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY MACHINE LEARNING, 2018-2030 (USD MILLION)
  • TABLE 208. AUSTRALIA ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY NATURAL LANGUAGE PROCESSING, 2018-2030 (USD MILLION)
  • TABLE 209. AUSTRALIA ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY APPLICATION AREAS, 2018-2030 (USD MILLION)
  • TABLE 210. AUSTRALIA ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY DEMAND-SIDE MANAGEMENT, 2018-2030 (USD MILLION)
  • TABLE 211. AUSTRALIA ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY ENERGY MANAGEMENT, 2018-2030 (USD MILLION)
  • TABLE 212. AUSTRALIA ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY GRID MANAGEMENT, 2018-2030 (USD MILLION)
  • TABLE 213. AUSTRALIA ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY PREDICTIVE MAINTENANCE, 2018-2030 (USD MILLION)
  • TABLE 214. AUSTRALIA ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY END USER, 2018-2030 (USD MILLION)
  • TABLE 215. AUSTRALIA ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY COMMERCIAL, 2018-2030 (USD MILLION)
  • TABLE 216. AUSTRALIA ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY INDUSTRIAL, 2018-2030 (USD MILLION)
  • TABLE 217. AUSTRALIA ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY RESIDENTIAL, 2018-2030 (USD MILLION)
  • TABLE 218. AUSTRALIA ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY UTILITIES, 2018-2030 (USD MILLION)
  • TABLE 219. CHINA ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY COMPONENT, 2018-2030 (USD MILLION)
  • TABLE 220. CHINA ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY HARDWARE, 2018-2030 (USD MILLION)
  • TABLE 221. CHINA ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY SERVICES, 2018-2030 (USD MILLION)
  • TABLE 222. CHINA ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY SOFTWARE, 2018-2030 (USD MILLION)
  • TABLE 223. CHINA ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY TECHNOLOGY TYPES, 2018-2030 (USD MILLION)
  • TABLE 224. CHINA ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY COMPUTER VISION, 2018-2030 (USD MILLION)
  • TABLE 225. CHINA ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY MACHINE LEARNING, 2018-2030 (USD MILLION)
  • TABLE 226. CHINA ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY NATURAL LANGUAGE PROCESSING, 2018-2030 (USD MILLION)
  • TABLE 227. CHINA ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY APPLICATION AREAS, 2018-2030 (USD MILLION)
  • TABLE 228. CHINA ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY DEMAND-SIDE MANAGEMENT, 2018-2030 (USD MILLION)
  • TABLE 229. CHINA ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY ENERGY MANAGEMENT, 2018-2030 (USD MILLION)
  • TABLE 230. CHINA ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY GRID MANAGEMENT, 2018-2030 (USD MILLION)
  • TABLE 231. CHINA ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY PREDICTIVE MAINTENANCE, 2018-2030 (USD MILLION)
  • TABLE 232. CHINA ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY END USER, 2018-2030 (USD MILLION)
  • TABLE 233. CHINA ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY COMMERCIAL, 2018-2030 (USD MILLION)
  • TABLE 234. CHINA ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY INDUSTRIAL, 2018-2030 (USD MILLION)
  • TABLE 235. CHINA ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY RESIDENTIAL, 2018-2030 (USD MILLION)
  • TABLE 236. CHINA ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY UTILITIES, 2018-2030 (USD MILLION)
  • TABLE 237. INDIA ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY COMPONENT, 2018-2030 (USD MILLION)
  • TABLE 238. INDIA ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY HARDWARE, 2018-2030 (USD MILLION)
  • TABLE 239. INDIA ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY SERVICES, 2018-2030 (USD MILLION)
  • TABLE 240. INDIA ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY SOFTWARE, 2018-2030 (USD MILLION)
  • TABLE 241. INDIA ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY TECHNOLOGY TYPES, 2018-2030 (USD MILLION)
  • TABLE 242. INDIA ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY COMPUTER VISION, 2018-2030 (USD MILLION)
  • TABLE 243. INDIA ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY MACHINE LEARNING, 2018-2030 (USD MILLION)
  • TABLE 244. INDIA ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY NATURAL LANGUAGE PROCESSING, 2018-2030 (USD MILLION)
  • TABLE 245. INDIA ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY APPLICATION AREAS, 2018-2030 (USD MILLION)
  • TABLE 246. INDIA ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY DEMAND-SIDE MANAGEMENT, 2018-2030 (USD MILLION)
  • TABLE 247. INDIA ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY ENERGY MANAGEMENT, 2018-2030 (USD MILLION)
  • TABLE 248. INDIA ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY GRID MANAGEMENT, 2018-2030 (USD MILLION)
  • TABLE 249. INDIA ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY PREDICTIVE MAINTENANCE, 2018-2030 (USD MILLION)
  • TABLE 250. INDIA ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY END USER, 2018-2030 (USD MILLION)
  • TABLE 251. INDIA ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY COMMERCIAL, 2018-2030 (USD MILLION)
  • TABLE 252. INDIA ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY INDUSTRIAL, 2018-2030 (USD MILLION)
  • TABLE 253. INDIA ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY RESIDENTIAL, 2018-2030 (USD MILLION)
  • TABLE 254. INDIA ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY UTILITIES, 2018-2030 (USD MILLION)
  • TABLE 255. INDONESIA ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY COMPONENT, 2018-2030 (USD MILLION)
  • TABLE 256. INDONESIA ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY HARDWARE, 2018-2030 (USD MILLION)
  • TABLE 257. INDONESIA ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY SERVICES, 2018-2030 (USD MILLION)
  • TABLE 258. INDONESIA ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY SOFTWARE, 2018-2030 (USD MILLION)
  • TABLE 259. INDONESIA ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY TECHNOLOGY TYPES, 2018-2030 (USD MILLION)
  • TABLE 260. INDONESIA ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY COMPUTER VISION, 2018-2030 (USD MILLION)
  • TABLE 261. INDONESIA ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY MACHINE LEARNING, 2018-2030 (USD MILLION)
  • TABLE 262. INDONESIA ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY NATURAL LANGUAGE PROCESSING, 2018-2030 (USD MILLION)
  • TABLE 263. INDONESIA ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY APPLICATION AREAS, 2018-2030 (USD MILLION)
  • TABLE 264. INDONESIA ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY DEMAND-SIDE MANAGEMENT, 2018-2030 (USD MILLION)
  • TABLE 265. INDONESIA ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY ENERGY MANAGEMENT, 2018-2030 (USD MILLION)
  • TABLE 266. INDONESIA ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY GRID MANAGEMENT, 2018-2030 (USD MILLION)
  • TABLE 267. INDONESIA ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY PREDICTIVE MAINTENANCE, 2018-2030 (USD MILLION)
  • TABLE 268. INDONESIA ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY END USER, 2018-2030 (USD MILLION)
  • TABLE 269. INDONESIA ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY COMMERCIAL, 2018-2030 (USD MILLION)
  • TABLE 270. INDONESIA ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY INDUSTRIAL, 2018-2030 (USD MILLION)
  • TABLE 271. INDONESIA ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY RESIDENTIAL, 2018-2030 (USD MILLION)
  • TABLE 272. INDONESIA ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY UTILITIES, 2018-2030 (USD MILLION)
  • TABLE 273. JAPAN ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY COMPONENT, 2018-2030 (USD MILLION)
  • TABLE 274. JAPAN ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY HARDWARE, 2018-2030 (USD MILLION)
  • TABLE 275. JAPAN ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY SERVICES, 2018-2030 (USD MILLION)
  • TABLE 276. JAPAN ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY SOFTWARE, 2018-2030 (USD MILLION)
  • TABLE 277. JAPAN ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY TECHNOLOGY TYPES, 2018-2030 (USD MILLION)
  • TABLE 278. JAPAN ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY COMPUTER VISION, 2018-2030 (USD MILLION)
  • TABLE 279. JAPAN ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY MACHINE LEARNING, 2018-2030 (USD MILLION)
  • TABLE 280. JAPAN ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY NATURAL LANGUAGE PROCESSING, 2018-2030 (USD MILLION)
  • TABLE 281. JAPAN ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY APPLICATION AREAS, 2018-2030 (USD MILLION)
  • TABLE 282. JAPAN ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY DEMAND-SIDE MANAGEMENT, 2018-2030 (USD MILLION)
  • TABLE 283. JAPAN ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY ENERGY MANAGEMENT, 2018-2030 (USD MILLION)
  • TABLE 284. JAPAN ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY GRID MANAGEMENT, 2018-2030 (USD MILLION)
  • TABLE 285. JAPAN ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY PREDICTIVE MAINTENANCE, 2018-2030 (USD MILLION)
  • TABLE 286. JAPAN ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY END USER, 2018-2030 (USD MILLION)
  • TABLE 287. JAPAN ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY COMMERCIAL, 2018-2030 (USD MILLION)
  • TABLE 288. JAPAN ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY INDUSTRIAL, 2018-2030 (USD MILLION)
  • TABLE 289. JAPAN ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY RESIDENTIAL, 2018-2030 (USD MILLION)
  • TABLE 290. JAPAN ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY UTILITIES, 2018-2030 (USD MILLION)
  • TABLE 291. MALAYSIA ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY COMPONENT, 2018-2030 (USD MILLION)
  • TABLE 292. MALAYSIA ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY HARDWARE, 2018-2030 (USD MILLION)
  • TABLE 293. MALAYSIA ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY SERVICES, 2018-2030 (USD MILLION)
  • TABLE 294. MALAYSIA ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY SOFTWARE, 2018-2030 (USD MILLION)
  • TABLE 295. MALAYSIA ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY TECHNOLOGY TYPES, 2018-2030 (USD MILLION)
  • TABLE 296. MALAYSIA ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY COMPUTER VISION, 2018-2030 (USD MILLION)
  • TABLE 297. MALAYSIA ARTIFICIAL INTELLIGENCE IN ENERGY MARKET SIZE, BY MACHINE LEARNING, 2018-2030 (USD MILLION)
  • TABLE 298. MALAYSIA ARTIFICIAL I