市場調査レポート

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1551309

エネルギーにおけるAI市場の2030年までの予測：コンポーネントタイプ別、展開タイプ別、用途別、エンドユーザー別、地域別の世界分析

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: 2024年09月06日
発行: Stratistics Market Research Consulting
ページ情報: 英文 200+ Pages
納期: 2～3営業日

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概要
図表
目次

概要

サンプル依頼リストに入れる

Stratistics MRCによると、世界のエネルギーにおけるAI市場は2024年に68億1,000万米ドルを占め、予測期間中のCAGRは19.4％で成長し、2030年には197億3,000万米ドルに達すると予測されています。

人工知能（AI）は、コスト削減、効率向上、プロセス最適化を通じてエネルギー産業を変革しています。人工知能（AI）技術は、配電網の管理を改善し、エネルギー需要を予測し、エネルギー生産を最大化するために利用されています。AIは、高度なアルゴリズムと機械学習を用いてセンサーやスマートグリッドからの大量のデータを分析することで、エネルギー消費のパターンを予測し、供給のリアルタイム調整を行うことができます。さらに、再生可能エネルギーの変動を制御し、エネルギーの安定供給を保証することで、AIは再生可能エネルギーの送電網への統合に重要な役割を果たします。

国際エネルギー機関（IEA）によれば、エネルギーにおけるAIの採用は、エネルギー効率の大幅な改善につながり、変化する需要と供給の状況にリアルタイムで適応できる、よりスマートなエネルギーシステムを実現する可能性があります。

高まるエネルギー効率への関心

世界のエネルギー消費量が増加の一途をたどるなか、より効果的なエネルギー管理への需要が高まっています。この需要に応えるための先導役となっているのが、人工知能（AI）技術です。人工知能（AI）は、エネルギー消費のパターンを予測し、エネルギー出力を最大化し、無駄なエネルギー支出を削減するツールを提供します。人工知能（AI）には、機械学習アルゴリズムを用いて、エネルギーシステムの非効率性を認識し、修正を提案し、需要の変動に自動反応を開始する能力があります。さらに、手元にある資源を最大限に活用することで、エネルギー・プロバイダーの運営コストを下げるだけでなく、温室効果ガス排出削減のための世界の取り組みにも貢献します。

法外な導入費用

エネルギー部門は人工知能（AI）から大きな恩恵を受けることができるが、多くの組織（特に小規模の公益事業者やエネルギー会社）は、AI技術を導入するための初期費用が手の届かないものであると感じるかもしれないです。AIの統合には、ソフトウェア、ハードウェア、有能な労働力への相当な投資が必要です。現在のインフラのアップグレード、データサイエンティストやAIの専門家の雇用やトレーニングへの投資、最先端のセンサーやデータ処理機器の購入など、企業にとって必要なものはすべて考えられます。さらに、AIアルゴリズムは特定のエネルギー用途向けにカスタマイズする必要があり、その作成と維持にはコストがかかります。

AIを活用した予知保全システムの構築

AIを活用した予知保全に関しては、エネルギー部門は多くの可能性を秘めています。発電所、送電線、再生可能エネルギー設備などのエネルギー・インフラの状態を常に監視することで、人工知能（AI）は故障が起こる前にメンテナンスの必要性を予測することができます。メンテナンスコストの削減に加え、資産の寿命が延び、ダウンタイムが減少します。さらに、予知保全におけるAIの活用は、運用の有効性を高めるだけでなく、エネルギーの生成と供給における安全性と信頼性も高める。

サイバーセキュリティへの脅威とリスク

エネルギー部門がAIへの依存を高めていることに関連して、大きなサイバーセキュリティ・リスクが存在します。人工知能（AI）システムは、発電所、配電網、エネルギーグリッドを制御する上でますます重要になってきています。AI主導のエネルギー・システムが攻撃に成功した場合、広範な停電や重要インフラへの被害、さらには国家安全保障への脅威が生じる可能性があります。ハッカーはAIアルゴリズムを改変して、機器の誤作動を引き起こしたり、エネルギー配給を危険にさらしたり、機密情報を盗み出したりすることができるかもしれないです。さらに、エネルギー・システムがよりデジタル的に統合され、依存性が高まるにつれて攻撃対象は拡大し、サイバー攻撃に対する防御の難易度は高まる。

COVID-19の影響：

COVID-19パンデミックは、エネルギーにおける人工知能（AI）市場に大きな影響を与えました。サプライチェーンの混乱、プロジェクトの遅延、ロックダウンや経済成長の鈍化によるエネルギー需要の一時的な落ち込みを引き起こしました。しかし、エネルギー企業が業務の合理化、遠隔監視能力の向上、将来のショックへの備えを模索する中、パンデミックは人工知能（AI）を含むデジタル技術の採用を早めることにもなった。さらに、より効果的なエネルギー管理と再生可能エネルギー源の統合の必要性がさらに高まったため、AIソリューションへの関心が危機の間に高まった。

予測期間中、ハードウェア・セグメントが最大となる見込み

エネルギーにおけるAI市場では、ハードウェア分野が最大のシェアを占めると予測されています。このセグメントには、センサー、CPU、ストレージ、その他の重要なインフラストラクチャなど、AIシステムの実装に必要な部品が含まれます。エネルギー管理、スマートグリッド、再生可能エネルギー統合におけるAIアプリケーションは、信頼性の高いデータ収集、リアルタイム処理、ストレージ機能を必要とするため、洗練されたハードウェアの必要性が高まっています。さらに、エネルギー企業は、AI主導型ソリューションの採用を増やしているため、現在、市場の支配的なセグメントとなっており、これが洗練された高性能ハードウェアの需要を押し上げています。

予測期間中、クラウドベースのセグメントが最も高いCAGRを予測

エネルギーにおけるAI市場のクラウドベースのソリューションセグメントは、CAGRが最も高いです。手頃な価格、拡張性、柔軟性によりクラウドコンピューティングの人気が高まっていることが、この成長の主な要因です。エネルギー企業は、クラウドベースのAIプラットフォームにより、オンプレミスの多くのインフラを必要とせずに、大量のデータと洗練されたアルゴリズムを利用できるようになった。さらに、クラウド・ソリューションは地理的な境界を越えたコラボレーションをサポートし、異種データ・ソースの統合を可能にするため、複雑なエネルギー・システムを管理し、エネルギー最適化や予知保全などの分野でイノベーションを促進する上で特に魅力的です。

最大のシェアを占める地域

エネルギーにおけるAI市場では、北米が最大のシェアを占めています。エネルギー部門が確立されていること、研究開発に多額の投資を行っていること、最先端の技術インフラを有していることなどが、この優位性の理由です。AI技術の採用は北米、特に米国で主要企業となっているが、これは官民からの多額の資金提供、大手テクノロジー会社や独創的な新興企業の強力な存在によるものです。さらに、この地域ではインフラの近代化、再生可能エネルギー源の統合、エネルギー効率の向上が重視されているため、AIソリューションの需要が高いです。

CAGRが最も高い地域：

エネルギーにおけるAI市場は、アジア太平洋地域で最も高いCAGRで成長しています。同地域の工業化の進展、エネルギー・インフラ投資の増加、エネルギー効率の改善と再生可能エネルギー源の導入を目的とした主要な政府プログラムが、この急成長の主な原動力となっています。増大するエネルギー需要を満たし、エネルギー・システムを更新するために、中国やインドのような国々がAI技術採用の基準を設定しています。さらに、スマートグリッドの開発、都市化、持続可能なエネルギー慣行の推進により、この地域でのAIの採用も加速しています。

無料のカスタマイズサービス：

本レポートをご購読のお客様には、以下の無料カスタマイズオプションのいずれかをご利用いただけます：

企業プロファイル
- 追加市場プレーヤーの包括的プロファイリング（3社まで）
- 主要企業のSWOT分析（3社まで）
地域セグメンテーション
- 顧客の関心に応じた主要国の市場推計・予測・CAGR（注：フィージビリティチェックによる）
競合ベンチマーキング
- 製品ポートフォリオ、地理的プレゼンス、戦略的提携に基づく主要企業のベンチマーキング

北米
- 米国
- カナダ
- メキシコ
欧州
- ドイツ
- 英国
- イタリア
- フランス
- スペイン
- その他欧州
アジア太平洋
- 日本
- 中国
- インド
- オーストラリア
- ニュージーランド
- 韓国
- その他アジア太平洋地域
南米
- アルゼンチン
- ブラジル
- チリ
- その他南米
中東・アフリカ
- サウジアラビア
- アラブ首長国連邦
- カタール
- 南アフリカ
- その他中東とアフリカ

第10章主な発展

契約、パートナーシップ、コラボレーション、合弁事業
買収と合併
新製品発売
事業拡大
その他の主要戦略

第11章企業プロファイリング

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

図表

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)

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

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

エネルギーにおけるAI市場の2030年までの予測： コンポーネントタイプ別、展開タイプ別、用途別、エンドユーザー別、地域別の世界分析

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

COVID-19の影響：

最大のシェアを占める地域

CAGRが最も高い地域：

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目次

第1章 エグゼクティブサマリー

第2章 序文

第3章 市場動向分析

第4章 ポーターのファイブフォース分析

第5章 世界のエネルギーにおけるAI市場：コンポーネントタイプ別

第6章 世界のエネルギーにおけるAI市場：展開タイプ別

第7章 世界のエネルギーにおけるAI市場：用途別

第8章 世界のエネルギーにおけるAI市場：エンドユーザー別

第9章 世界のエネルギーにおけるAI市場：地域別

第10章 主な発展

第11章 企業プロファイリング