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1551309

2030 年能源市場人工智慧預測：按組件類型、部署類型、應用、最終用戶和地區進行的全球分析

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

價格

根據 Stratistics MRC 的數據，2024 年全球人工智慧能源市場規模將達到 68.1 億美元，預計到 2030 年將達到 197.3 億美元，預測期內複合年成長率為 19.4%。

人工智慧 (AI) 正在透過降低成本、提高效率和最佳化流程來改變能源產業。人工智慧 (AI) 技術被用來改善電網管理、預測能源需求並最大限度地提高能源產量。透過使用先進的演算法和機器學習來分析來自感測器和智慧電網的大量資料，人工智慧可以預測能源消耗模式並即時調整供應。此外，透過控制可再生能源波動、確保能源穩定供應，人工智慧將在可再生能源併網中發揮關鍵作用。

國際能源總署（IEA）表示，在能源領域採用人工智慧有可能顯著提高能源效率，並實現更智慧的能源系統，能夠即時適應不斷變化的供需條件。

人們對能源效率的興趣日益濃厚

隨著全球能源消費量持續上升，對更有效的能源管理的需求不斷增加。人工智慧 (AI) 技術在滿足這一需求方面處於領先地位。人工智慧 (AI) 提供了預測能源消耗模式、最大化能源產出並減少能源浪費的工具。人工智慧 (AI) 能夠使用機器學習演算法來識別能源系統的低效率、提案修改建議並對需求波動啟動自動回應。此外，透過充分利用現有資源，我們不僅可以降低能源供應商的營運成本，還可以為全球減少溫室氣體排放的努力做出貢獻。

實施成本過高

能源產業可以從人工智慧 (AI) 中受益匪淺，但許多組織（特別是小型公共產業和能源公司）發現實施人工智慧技術的初始成本遙不可及。整合人工智慧需要對軟體、硬體和熟練的勞動力進行大量投資。升級您目前的基礎設施、投資僱用和培訓資料科學家和人工智慧專家、購買尖端感測器和資料處理設備等等都可以滿足您公司的需求。此外，人工智慧演算法必須針對特定能源應用進行客製化，並且創建和維護成本高昂。

使用人工智慧建構預測維修系統

在人工智慧驅動的預測性維護方面，能源產業具有巨大的潛力。透過持續監控發電廠、輸電線路和可再生能源設備等能源基礎設施的健康狀況，人工智慧 (AI) 可以在故障發生之前預測維護需求。除了降低維護成本外，還可以延長資產使用壽命並減少停機時間。此外，在預測性維護中使用人工智慧不僅可以提高營運效率，還可以提高能源生產和供應的安全性和可靠性。

網路安全威脅與風險

能源產業對人工智慧的依賴日益增加，存在重大的網路安全風險。人工智慧 (AI) 系統在控制發電廠、配電網路和能源網路方面變得越來越重要。對人工智慧主導的能源系統的成功攻擊可能會導致大規模停電、關鍵基礎設施受損，甚至對國家安全構成威脅。駭客可能能夠修改人工智慧演算法，導致設備故障、危及能源發行或竊取敏感資訊。此外，隨著能源系統變得更加數位化整合和依賴，攻擊面將會擴大，網路攻擊將變得更加難以防禦。

COVID-19 的影響：

COVID-19 大流行對能源領域的人工智慧 (AI) 市場產生了重大影響。供應鏈中斷、計劃延誤、封鎖和經濟成長放緩導致能源需求暫時下降。但疫情也加速了包括人工智慧 (AI) 在內的數位技術的採用，因為能源公司尋求簡化業務、提高遠端監控能力並為未來的衝擊做好準備。此外，在危機期間，人們對人工智慧解決方案的興趣增加，因為對更有效的能源管理和再生能源來源整合的需求變得更加強烈。

預計硬體領域將在預測期內成為最大的領域

預計硬體領域將佔據能源領域人工智慧市場的最大佔有率。該部分包括實施人工智慧系統所需的零件，例如感測器、CPU、儲存和其他關鍵基礎設施。能源管理、智慧電網和可再生能源整合中的人工智慧應用需要可靠的資料收集、即時處理和儲存能力，增加了對複雜硬體的需求。此外，能源公司現在已成為市場的主導部分，因為它們擴大採用人工智慧主導的解決方案，這推動了對複雜、高效能硬體的需求。

雲端基礎的細分市場預計在預測期內複合年成長率最高

能源市場人工智慧的雲端基礎的解決方案領域的複合年成長率最高。雲端運算因其經濟性、擴充性和靈活性而日益普及，是這一成長的關鍵驅動力。雲端基礎的人工智慧平台使能源公司能夠利用大量資料和複雜的演算法，而無需太多的本地基礎設施。此外，雲端解決方案支援跨地理邊界的協作並實現不同資料來源的整合，使組織能夠管理複雜的能源系統並在能源最佳化和預測性維護等領域進行創新，這在促進方面特別有吸引力。

比最大的地區

北美在能源人工智慧市場中佔有最大佔有率。這一優勢得益於完善的能源部門、大量的研發投資以及最先進的技術基礎設施。由於大量的公共和私人資金以及大型科技公司和創意新興企業的強大存在，人工智慧技術的採用已成為北美，特別是美國的主要企業。此外，隨著該地區專注於基礎設施現代化、整合再生能源來源和提高能源效率，人工智慧解決方案的需求量很大。

複合年成長率最高的地區：

能源領域的人工智慧市場正以亞太地區最高的複合年成長率成長。該地區工業化程度的提高、能源和基礎設施投資的增加以及旨在提高能源效率和引入再生能源來源的重大政府計劃是這一快速成長的主要驅動力。中國和印度等國家正在製定採用人工智慧技術的標準，以滿足不斷成長的能源需求和更新能源系統。此外，智慧電網、都市化的發展和永續能源實踐的推廣也加速了人工智慧在該地區的採用。

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目錄

第1章執行摘要

第2章 前言

  • 概述
  • 相關利益者
  • 調查範圍
  • 調查方法
    • 資料探勘
    • 資料分析
    • 資料檢驗
    • 研究途徑
  • 研究資訊來源
    • 主要研究資訊來源
    • 二次研究資訊來源
    • 先決條件

第3章市場趨勢分析

  • 促進因素
  • 抑制因素
  • 機會
  • 威脅
  • 應用分析
  • 最終用戶分析
  • 新興市場
  • COVID-19 的影響

第4章波特五力分析

  • 供應商的議價能力
  • 買方議價能力
  • 替代品的威脅
  • 新進入者的威脅
  • 競爭公司之間的敵對關係

第5章全球能源人工智慧市場：按組件類型

  • 硬體
  • 解決方案
  • 服務

第6章全球能源人工智慧市場：按部署類型

  • 本地
  • 雲端基礎

第7章 全球能源人工智慧市場：依應用分類

  • 機器人技術
  • 能源管理
  • 可再生能源管理
  • 需求預測
  • 預測性維護
  • 網格最佳化
  • 安全保障
  • 基礎設施
  • 其他用途

第8章 全球能源人工智慧市場：依最終用戶分類

  • 發電
  • 石油和天然氣
  • 可再生能源
  • 公共事業
  • 其他最終用戶

第9章全球能源人工智慧市場：按地區

  • 北美洲
    • 美國
    • 加拿大
    • 墨西哥
  • 歐洲
    • 德國
    • 英國
    • 義大利
    • 法國
    • 西班牙
    • 其他歐洲國家
  • 亞太地區
    • 日本
    • 中國
    • 印度
    • 澳洲
    • 紐西蘭
    • 韓國
    • 其他亞太地區
  • 南美洲
    • 阿根廷
    • 巴西
    • 智利
    • 南美洲其他地區
  • 中東/非洲
    • 沙烏地阿拉伯
    • 阿拉伯聯合大公國
    • 卡達
    • 南非
    • 其他中東和非洲

第10章 主要進展

  • 合約、夥伴關係、合作和合資企業
  • 收購和合併
  • 新產品發布
  • 業務拓展
  • 其他關鍵策略

第11章 公司概況

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

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

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

Market Dynamics:

Driver:

Growing interest in energy efficiency

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

Restraint:

Exorbitant implementation expenses

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

Opportunity:

Creating AI-powered predictive maintenance systems

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

Threat:

Threats and risks to cybersecurity

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

Covid-19 Impact:

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

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

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

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

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

Region with largest share:

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

Region with highest CAGR:

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

Key players in the market

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

Key Developments:

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

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

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

Component Types Covered:

  • Hardware
  • Solutions
  • Services

Deployment Types Covered:

  • On-premise
  • Cloud-based

Applications Covered:

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

End Users Covered:

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

Regions Covered:

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

What our report offers:

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

Free Customization Offerings:

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

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

Table of Contents

1 Executive Summary

2 Preface

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

3 Market Trend Analysis

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

4 Porters Five Force Analysis

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

5 Global AI in Energy Market, By Component Type

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

6 Global AI in Energy Market, By Deployment Type

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

7 Global AI in Energy Market, By Application

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

8 Global AI in Energy Market, By End User

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

9 Global AI in Energy Market, By Geography

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

10 Key Developments

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

11 Company Profiling

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

List of Tables

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