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能源市場人工智慧按組件、技術類型、應用領域和最終用戶分類 - 2025 年至 2030 年全球預測

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個工作天內

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能源領域的人工智慧市場規模預計在 2024 年將達到 99.2 億美元，2025 年將達到 123.6 億美元，複合年成長率為 25.37%，到 2030 年將達到 385.5 億美元。

主要市場統計數據
基準年 2024 年 99.2億美元
預計 2025 年 123.6億美元
預測年份 2030 385.5億美元
複合年成長率（%） 25.37％

人工智慧正快速重塑能源格局，帶來業務效率、策略規劃、系統可靠性等方面的深刻變化。近年來，先進的機器學習技術與能源管理方法的整合帶來了巨大的機會。能源公司正在利用人工智慧來最大限度地減少低效率，並透過更智慧的電網管理和預測性維護來推動永續性。重新關注能源領域的數位轉型也推動了能源需求和供應預測更強大的分析，使營運商能夠更好地應對動態的市場條件。

人工智慧在能源領域的重要性日益增加，從最佳化發電到實現對電網健康狀況的即時監控。從可再生能源的整合到傳統發電廠的營運，該行業的每個方面都受益於資料主導的洞察。這種動態不僅帶來了績效的提高，而且還帶來了優先考慮永續性和彈性的新經營模式。能源相關人員擴大投資於人工智慧解決方案，以釋放先前未開發的營運智慧蘊藏量，而高階分析則推動集體成本節約和增強決策能力。

本報告全面介紹了人工智慧如何改變能源產業。它詳細介紹了決策者可以採取的關鍵創新、不斷發展的市場結構和現實策略。在數位科技決定競爭力的時代，了解人工智慧在能源生產、分配和消費中的作用至關重要。以下我們將深入探討推動這些技術進步的變革性轉變、細分細節、區域差異和主要企業。

重新定義能源格局的轉型

隨著數位化的進步和人工智慧的日益普及，能源產業正在經歷前所未有的變化，並顯著轉向技術主導的解決方案。在過去的十年中，傳統方法逐漸讓位給最佳化電網管理和增強能源儲存解決方案的創新預測系統。這種轉變是多方面壓力的結果，包括不斷成長的能源需求、環境限制和全球對可再生能源整合的推動。

數位轉型推動了能源領域的操作技術和資訊技術的融合。強大的機器學習模型已成為主流，使組織能夠更準確地預測消費模式，即時分析資產績效，並顯著減少非計劃性停機時間。在這種情況下，重點是採取主動方法，將重點從被動解決方案轉移到預測問題並在問題變得嚴重之前緩解問題。

自動控制系統和智慧感測器的引入使企業能夠從海量資料中獲得可行的見解。電腦視覺、自然語言處理和機器人技術的整合不僅實現了常規流程的自動化，還提高了安全性和業務效率。此外，在決策流程中採用尖端的人工智慧技術重新定義了營運基準，並為能源發行的可靠性和效率設定了新的標準。這些變革性轉變正在影響當今的投資策略、營運規劃和公共，標誌著產業發展的關鍵曲折點。

市場成長的關鍵細分洞察

市場區隔提供了多樣化的視角來評估人工智慧在能源領域的影響。在組件層面，透過硬體、服務和軟體的互動來探索市場。硬體解決方案包括先進的控制器、強大的處理器和複雜的感測器陣列，有助於跨能源網路的資料採集。服務組件包括諮詢服務、部署和整合專業知識以及強大的支援和維護框架，以確保您的系統無縫運作。軟體部門涵蓋分析解決方案和綜合能源管理軟體，強調資料解釋和敏捷控制機制在現代能源營運中的重要性。

為了進一步細分，我們需要了解技術類型。此觀點主要關注電腦視覺、機器學習、自然語言處理和機器人等專業應用。在電腦視覺領域，影像識別和視訊分析功能是增強監控和資產追蹤的驅動力。機器學習細分為強化學習、監督學習和無監督學習。這些調查方法增強了預測分析和自適應系統反應。同樣，自然語言處理涵蓋語言翻譯和高級語音辨識，有助於增強控制室的人機介面。

按應用領域細分市場可以提供更深入的見解。這包括需求面管理、能源管理、電網管理和預測性維護等關鍵領域。需求面管理顯示需求預測和能源效率最佳化等因素極為重要。能源管理將變得更加細緻入微，需量反應、能源交易和負載預測策略使營運商能夠平衡波動的消費者需求和供應。電網管理強調電網監控和微電網開發的重要性，而預測性維護則著重於狀態監控和故障前預測，以減少停機時間。

最後，最終用戶的分析揭示了影響市場動態的人口統計多樣化需求模式。商業建築的目標是辦公大樓和購物中心，而工業應用則涵蓋採礦、石油和天然氣等領域。在住宅應用方面，該報告重點關注能源儲存系統和智慧家庭創新的興起，使最終用戶能夠有效地管理消費量。公共產業部門透過檢查配電系統營運商和發電公司，進一步細分其在能源生態系統中的作用。這種全面的細分有助於了解頻譜的人工智慧應用，並客製化解決方案以有效滿足特定的市場需求。

目錄

第 1 章 簡介

第2章調查方法

第3章執行摘要

第4章 市場概況

第5章 市場洞察

  • 市場動態
    • 驅動程式
      • 人工智慧智慧電網技術的應用不斷擴大，以提高能源效率和永續性目標
      • 對人工智慧驅動的預測性維護解決方案的需求不斷增加，以降低能源基礎設施的營運成本
    • 限制因素
      • 高昂的實施成本和複雜的整合流程限制了人工智慧在能源系統中的應用
    • 機會
      • 開發人工智慧能源儲存解決方案，解決再生能源來源的間歇性問題
      • 擴大人工智慧在可再生能源管理的應用，以最佳化資源利用率和電網穩定性
    • 任務
      • 資料隱私問題和監管不確定性影響人工智慧在能源應用中的擴充性
  • 市場區隔分析
    • 組件：驅動能源領域人工智慧系統的硬體組件
    • 最終用戶：工業領域用於能源最佳化的人工智慧應用
  • 波特五力分析
  • PESTEL 分析
    • 政治的
    • 經濟
    • 社會的
    • 技術的
    • 合法的
    • 環境

第6章 能源領域人工智慧市場（按組成部分）

  • 硬體
    • 控制器
    • 處理器
    • 感應器
  • 服務
    • 諮詢服務
    • 部署和整合
    • 支援和維護
  • 軟體
    • 分析解決方案
    • 能源管理軟體

第7章 能源市場中的人工智慧（依技術類型）

  • 電腦視覺
    • 影像識別
    • 影片分析
  • 機器學習
    • 強化學習
    • 監督學習
    • 無監督學習
  • 自然語言處理
    • 語言翻譯
    • 語音辨識
  • 機器人

第 8 章 能源領域人工智慧市場（按應用）

  • 需求面管理
    • 需求預測
    • 最佳化能源效率
  • 能源管理
    • 需量反應
    • 能源交易
    • 負荷預測
  • 電網管理
    • 電網監控
    • 微型電網
  • 預測性維護
    • 狀態監測
    • 故障預測

第9章 能源領域人工智慧市場（按最終用戶分類）

  • 商業的
    • 辦公大樓
    • 購物中心
  • 產業
    • 礦業
    • 石油和天然氣
  • 住宅
    • 能源儲存系統
    • 智慧家庭
  • 實用工具
    • 配電公司
    • 發電公司

第 10 章 美洲能源領域人工智慧市場

  • 阿根廷
  • 巴西
  • 加拿大
  • 墨西哥
  • 美國

第 11 章 亞太能源領域人工智慧市場

  • 澳洲
  • 中國
  • 印度
  • 印尼
  • 日本
  • 馬來西亞
  • 菲律賓
  • 新加坡
  • 韓國
  • 台灣
  • 泰國
  • 越南

第 12 章。

  • 丹麥
  • 埃及
  • 芬蘭
  • 法國
  • 德國
  • 以色列
  • 義大利
  • 荷蘭
  • 奈及利亞
  • 挪威
  • 波蘭
  • 卡達
  • 俄羅斯
  • 沙烏地阿拉伯
  • 南非
  • 西班牙
  • 瑞典
  • 瑞士
  • 土耳其
  • 阿拉伯聯合大公國
  • 英國

第13章 競爭格局

  • 2024 年市場佔有率分析
  • FPNV 定位矩陣，2024 年
  • 競爭情境分析
  • 戰略分析與建議

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