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AI市場 (～2035年)：提供区分・技術・展開・用途・エンドユーザー・地域別の産業動向および世界の予測

Artificial Intelligence Market, Till 2035: Distribution by Type of Offering, Type of Technology, Type of Deployment, Type of Application Type of End User, Geographical Regions : Industry Trends and Global Forecasts

出版日
ページ情報
英文 174 Pages
納期
2～10営業日
カスタマイズ可能
価格
価格表記: USDを日本円(税抜)に換算
本日の銀行送金レート: 1USD=146.35円
AI市場 (～2035年)：提供区分・技術・展開・用途・エンドユーザー・地域別の産業動向および世界の予測
出版日: 2025年05月08日
発行: Roots Analysis
ページ情報: 英文 174 Pages
納期: 2～10営業日
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  • 全表示
  • 概要
  • 図表
  • 目次
概要

世界のAIの市場規模は、現在の2,736億米ドルから、予測期間中はCAGR 30.84%で推移し、2035年には5兆2,670億米ドルに成長すると予測されています。

Artificial Intelligence Market-IMG1

AIの市場機会：セグメント別

提供区分別

  • ハードウェア
  • ソフトウェア
  • サービス

処理タイプ別

  • クラウド
  • エッジ

技術タイプ別

  • コンピュータビジョン
  • コンテクストアウェアAI
  • エキスパートシステム
  • 機械学習
  • 自然言語処理
  • ロボティクスプロセス自動化

展開別

  • クラウドベース
  • オンプレミス

用途別

  • 自動顧客サービス
  • 不正検知・リスク管理
  • ヘルスケア診断
  • マーケティング＆セールス
  • 予測分析
  • ロボティクス
  • サプライチェーン最適化

エンドユーザー別

  • 自動車
  • BFSI
  • エネルギー・ユーティリティ
  • 政府機関
  • ヘルスケア
  • 製造
  • 小売・eコマース
  • 通信

地域別

  • 北米
  • 米国
  • カナダ
  • メキシコ
  • その他の北米諸国
  • 欧州
  • オーストリア
  • ベルギー
  • デンマーク
  • フランス
  • ドイツ
  • アイルランド
  • イタリア
  • オランダ
  • ノルウェー
  • ロシア
  • スペイン
  • スウェーデン
  • スイス
  • 英国
  • その他の欧州諸国
  • アジア
  • 中国
  • インド
  • 日本
  • シンガポール
  • 韓国
  • その他のアジア諸国
  • ラテンアメリカ
  • ブラジル
  • チリ
  • コロンビア
  • ベネズエラ
  • その他のラテンアメリカ諸国
  • 中東・北アフリカ
  • エジプト
  • イラン
  • イラク
  • イスラエル
  • クウェート
  • サウジアラビア
  • アラブ首長国連邦
  • その他の中東・北アフリカ諸国
  • 世界のその他の地域
  • オーストラリア
  • ニュージーランド
  • その他の国

技術の進化が続く中、AIは急速に進歩しており、ほぼすべての業種で広く導入されています。医療、金融、教育、製造業といった産業は、この技術を活用してデータ駆動型のプロセスを強化し、反復的な業務を管理することで、世界のAI市場の拡大の可能性を高めています。これまでの数年間にわたり、産業オートメーションの進展、IoT機器の利用拡大、そして継続的な技術革新が、業界関係者に新たな事業機会をもたらしてきました。その結果、さまざまな業界の進化するニーズに対応するため、ステークホルダーはAIの研究開発への大規模な投資を行っています。

汎用人工知能 (AGI) の台頭により、今後の予測期間において、世界のAI市場は堅調な成長が見込まれています。

提供区分別市場シェア

提供区分別では現在、ソフトウェアの部門が市場の大半のシェアを占めています。これは、自然言語処理、コンピュータビジョン、エッジAI、機械学習、ディープラーニング、ロボット工学など、医療、自動車、金融などさまざまな分野で活用されている幅広い用途に起因しています。一方で、クラウドベースの部門は予測期間中により高いCAGRで成長すると予測されています。

技術タイプ別市場シェア

技術別では現在、機械学習の部門が市場の大半のシェアを占めています。これは、機械学習がAIソリューションの基本コンポーネントとして機能し、コンピュータがデータから学習し、パターンを識別し、意思決定を行うモデルの開発を可能にするという事実に起因しています。一方で、自然言語処理の部門は予測期間中により高いCAGRで成長すると予測されています。

展開別市場シェア

展開別では現在、クラウドベースの部門が市場の大半のシェアを占めており、将来的にも高いCAGRで成長すると予測されています。これは、クラウドベースのシステムが拡張性と柔軟性を備えているため、企業がニーズに応じてAIリソースを調整できることに起因しています。さらに、クラウドベースのオプションは費用対効果が高いため、予算が限られている中小企業でも利用しやすく、人気が高まっています。

用途別市場シェア

用途別では現在、マーケティング＆セールスの部門が市場の大半のシェアを占めています。これは、視聴者ターゲティングと顧客エンゲージメント向上のためにAI技術が広く使用されていることに起因しています。さらに、企業はパーソナライズされたマーケティング戦略を強化し、AI主導の顧客洞察と分析を得るためにAIツールを活用しています。一方で、自動顧客サービスの部門は予測期間中により高いCAGRで成長すると予測されています。

エンドユーザータイプ別市場シェア

エンドユーザー別では現在、BFSIの部門が市場の大半のシェアを占めています。これは、業務の最適化、大量の財務データの管理、不正行為の検出、パーソナライズされた顧客体験の提供などを目的としたAI技術の利用が増加しているためと考えられます。一方で、医療部門は予測期間中により高いCAGRで成長すると予測されています。

当レポートでは、世界のAI市場の動向を調査し、 市場概要、背景、市場影響因子の分析、市場規模の推移・予測、各種区分・地域別の詳細分析、競合情勢、主要企業のプロファイルなどをまとめています。

目次

第1章 序文

第2章 調査手法

第3章 経済およびその他のプロジェクト固有の検討事項

第4章 マクロ経済指標

  • 概要
  • 市場力学

第5章 エグゼクティブサマリー

第6章 イントロダクション

  • 概要
  • AI市場の概要
  • 将来の展望

第7章 競合情勢

  • 概要
  • AI市場の情勢

第8章 企業プロファイル

  • 概要
  • Alibaba Cloud*
  • AMD
  • AMD
  • Arrow AI
  • AWS
  • Baidu
  • BMI
  • Cisco
  • DeepL
  • Dialpad
  • Glean
  • Google
  • Golden Omega
  • HPE
  • HQE System
  • Koninklijke
  • Huawei
  • Inbenta
  • Intel
  • Meta
  • Microsoft
  • Moveworks
  • NVIDIA
  • OpenAI
  • Oracle
  • Qualcomm
  • Salesforce
  • SAP
  • Seimens

第9章 バリューチェーン分析

第10章 SWOT分析

第11章 世界のAI市場

  • 概要
  • 主要な前提と調査手法
  • 市場に影響を与える動向の混乱
  • 世界のAI市場：これまでの動向と予測
  • 多変量シナリオ分析
  • 主要な市場セグメンテーション

第12章 提供区分別の市場機会

  • 概要
  • 主要な前提と調査手法
  • 収益シフト分析
  • 市場変動分析
  • 浸透成長 (PG) マトリックス
  • ハードウェア向けAI市場：これまでの動向と予測
  • ソフトウェア向けAI市場：これまでの動向と予測
  • サービス向けAI市場：これまでの動向と予測
  • データの三角測量と検証

第13章 技術別の市場機会

  • 概要
  • 主要な前提と調査手法
  • 収益シフト分析
  • 市場変動分析
  • 浸透成長 (PG) マトリックス
  • コンピュータービジョン向けAI市場：これまでの動向と予測
  • コンテキストアウェアAI向けAI市場：これまでの動向と予測
  • エキスパートシステム向けAI市場：これまでの動向と予測
  • 機械学習向けAI市場：これまでの動向と予測
  • 自然言語処理向けAI市場：これまでの動向と予測
  • ロボティクスプロセスオートメーション (RPA) 向けAI市場：これまでの動向と予測
  • データの三角測量と検証

第14章 展開別の市場機会

  • 概要
  • 主要な前提と調査手法
  • 収益シフト分析
  • 市場変動分析
  • 浸透成長 (PG) マトリックス
  • クラウドベースAI市場：これまでの動向と予測
  • オンプレミス向けAI市場：これまでの動向と予測
  • データの三角測量と検証

第15章 用途別の市場機会

  • 概要
  • 主要な前提と調査手法
  • 収益シフト分析
  • 市場変動分析
  • 浸透成長 (PG) マトリックス
  • 自動顧客サービス向けAI市場：これまでの動向と予測
  • 不正検出およびリスク管理のためのAI市場：これまでの動向と予測
  • ヘルスケア診断向けAI市場：これまでの動向と予測
  • マーケティングとセールスのためのAI市場：これまでの動向と予測
  • 予測分析のためのAI市場：これまでの動向と予測
  • ロボット向けAI市場：これまでの動向と予測
  • サプライチェーン最適化のためのAI市場：これまでの動向と予測
  • データの三角測量と検証

第16章 エンドユーザー別の市場機会

  • 概要
  • 主要な前提と調査手法
  • 収益シフト分析
  • 市場変動分析
  • 浸透成長 (PG) マトリックス
  • 自動車向けAI市場：これまでの動向と予測
  • BFSI向けAI市場：これまでの動向と予測
  • エネルギー・公益事業向けAI市場：これまでの動向と予測
  • 政府向けAI市場：これまでの動向と予測
  • ヘルスケア向けAI市場：これまでの動向と予測
  • 製造業向けAI市場：これまでの動向と予測
  • 小売・Eコマース向けAI市場：これまでの動向と予測
  • 通信におけるAI市場：これまでの動向と予測
  • その他向けAI市場：これまでの動向と予測
  • データの三角測量と検証

第17章 北米におけるAIの市場機会

  • 概要
  • 主要な前提と調査手法
  • 収益シフト分析
  • 市場変動分析
  • 浸透成長 (PG) マトリックス
  • 北米のAI市場：これまでの動向と予測
  • データの三角測量と検証

第18章 欧州におけるAIの市場機会

  • 概要
  • 主要な前提と調査手法
  • 収益シフト分析
  • 市場変動分析
  • 浸透成長 (PG) マトリックス
  • 欧州のAI市場：これまでの動向と予測
  • データの三角測量と検証

第19章 アジアにおけるAIの市場機会

  • 概要
  • 主要な前提と調査手法
  • 収益シフト分析
  • 市場変動分析
  • 浸透成長 (PG) マトリックス
  • アジアのAI市場：これまでの動向と予測
  • データの三角測量と検証

第20章 中東・北アフリカ (MENA) におけるAIの市場機会

  • 概要
  • 主要な前提と調査手法
  • 収益シフト分析
  • 市場変動分析
  • 浸透成長 (PG) マトリックス
  • 中東・北アフリカ (MENA) のAI市場：これまでの動向と予測
  • データの三角測量と検証

第21章 ラテンアメリカにおけるAIの市場機会

  • 概要
  • 主要な前提と調査手法
  • 収益シフト分析
  • 市場変動分析
  • 浸透成長 (PG) マトリックス
  • ラテンアメリカのAI市場：これまでの動向と予測
  • データの三角測量と検証

第22章 世界のその他の地域におけるAIの市場機会

  • 概要
  • 主要な前提と調査手法
  • 収益シフト分析
  • 市場変動分析
  • 浸透成長 (PG) マトリックス
  • 世界のその他の地域におけるAI市場：これまでの動向と予測
  • データの三角測量と検証

第23章 表形式データ

第24章 企業・団体一覧

第25章 カスタマイズの機会

第26章 ROOTSサブスクリプションサービス

第27章 著者詳細

図表

List of Tables

    • 24.6.2. Middle East and Africa Battery Management System Market for Electric Vehicles (Value, YoY Growth): Historical Trends (Since 2018) and Forecasted Estimates (Till 2035)
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目次
Product Code: RAICT300147

Artificial Intelligence Market Overview

As per Roots Analysis, the global artificial intelligence market size is estimated to grow from USD 273.6 billion in the current year to USD 5,267 billion by 2035, at a CAGR of 30.84% during the forecast period, till 2035.

Artificial Intelligence Market - IMG1

The opportunity for artificial intelligence market has been distributed across the following segments:

Type of Offering

  • Hardware
  • Software
  • Service

Type of Processing

  • Cloud
  • Edge

Type of Technology

  • Computer Vision
  • Context-Aware AI
  • Experts Systems
  • Machine Learning
  • Natural Language Processing
  • Robotics Process Automation

Type of Deployment

  • Cloud-based
  • On-Premises

Type of Application

  • Automated Customer Service
  • Fraud Detection & Risk Management
  • Healthcare Diagnostics
  • Marketing & Sales
  • Predictive Analytics
  • Robotics
  • Supply Chain Optimization

Type of End User

  • Automotive
  • BFSI
  • Energy & Utilities
  • Government
  • Healthcare
  • Manufacturing
  • Retail & E-Commerce
  • Telecommunication

Geographical Regions

  • North America
  • US
  • Canada
  • Mexico
  • Other North American countries
  • Europe
  • Austria
  • Belgium
  • Denmark
  • France
  • Germany
  • Ireland
  • Italy
  • Netherlands
  • Norway
  • Russia
  • Spain
  • Sweden
  • Switzerland
  • UK
  • Other European countries
  • Asia
  • China
  • India
  • Japan
  • Singapore
  • South Korea
  • Other Asian countries
  • Latin America
  • Brazil
  • Chile
  • Colombia
  • Venezuela
  • Other Latin American countries
  • Middle East and North Africa
  • Egypt
  • Iran
  • Iraq
  • Israel
  • Kuwait
  • Saudi Arabia
  • UAE
  • Other MENA countries
  • Rest of the World
  • Australia
  • New Zealand
  • Other countries

ARTIFICIAL INTELLIGENCE MARKET: GROWTH AND TRENDS

Artificial Intelligence (AI) refers to a wide area of computer science focused on developing machines that can execute tasks typically requiring human intelligence. This technology features various capabilities, including speaking, seeing, language comprehension and translation, and data analysis, marking it as one of the groundbreaking developments in the digital age. Additionally, it is worth mentioning that AI is a broad term that includes a variety of technologies, such as machine learning, deep learning, computer vision, and natural language processing.

As technology continues to evolve, AI is advancing quickly and is being widely adopted across almost all business sectors. Industries such as healthcare, finance, education, and manufacturing are utilizing this technology to enhance their data-driven processes and manage repetitive tasks, boosting the potential expansion of the global AI market. Throughout the years, the increasing implementation of industrial automation, the growing use of IoT devices, and ongoing technological progress have created new opportunities for industry participants. Consequently, stakeholders are making significant investments in AI research and development to address the evolving requirements of various sectors.

Driven by the rise of artificial general intelligence (AGI), the global artificial intelligence market is expected to grow at a healthy pace during the forecast period.

ARTIFICIAL INTELLIGENCE MARKET: KEY SEGMENTS

Market Share by Type of Offering

Based on the type of offering, the global artificial intelligence market is segmented into AI hardware, software, and service offerings. According to our estimates, currently, software segment captures the majority share of the market. This can be attributed to the wide range of applications, including natural language processing, computer vision, edge AI, machine learning, deep learning, and robotics, which are utilized across various sectors such as healthcare, automotive, and finance. However, cloud-based segment is anticipated to grow at a higher CAGR during the forecast period.

Market Share by Type of Technology

Based on the type of technology, the artificial intelligence market is segmented into computer vision, context-aware AI, experts systems, machine learning, natural language processing, and robotics process automation. According to our estimates, currently, machine learning segment captures the majority share of the market. This can be attributed to the fact that machine learning serves as a fundamental component of AI solutions, enabling the development of models that allow computers to learn from data, identify patterns, and make decisions. However, natural language processing segment is anticipated to grow at a higher CAGR during the forecast period.

Market Share by Type of Deployment

Based on the type of deployment, the artificial intelligence market is segmented into cloud-based and on-premises. According to our estimates, currently, cloud-based segment captures the majority share of the market; further, this segment is anticipated to grow at a higher CAGR in the future. This can be attributed to scalability and flexibility of cloud-based systems, allowing organizations to adjust AI resources based on their needs. Additionally, the cost-effectiveness of cloud-based options makes them increasingly popular and accessible to small and medium-sized enterprises with limited budgets, enabling them to take advantage of AI-as-a-service offerings at a manageable price.

Market Share by Type of Application

Based on the type of application, the artificial intelligence market is segmented into automated customer service, fraud detection & risk management, healthcare diagnostics, marketing & sales, predictive analytics, robotics, and supply chain optimization. According to our estimates, currently, marketing & sales segment captures the majority share of the market. This can be attributed to the prevalent use of AI technology for audience targeting and improving customer engagement. Additionally, companies are utilizing AI tools to enhance personalized marketing strategies and gain AI-driven customer insights and analytics. However, automated customer service segment is anticipated to grow at a higher CAGR during the forecast period.

Market Share by Type of End User

Based on the type of end user, the artificial intelligence market is segmented into automotive, BFSI, energy & utilities, government, healthcare, manufacturing, retail & e-commerce, telecommunication, and others. According to our estimates, currently, BFSI segment captures the majority share of the market. This can be attributed to its increased use of AI technology to optimize operations, manage large volumes of financial data, detect fraud, and provide personalized customer experiences. However, healthcare segment is anticipated to grow at a higher CAGR during the forecast period.

Market Share by Geographical Regions

Based on the geographical regions, the artificial intelligence market is segmented into North America, Europe, Asia, Latin America, Middle East and North Africa, and Rest of the World. According to our estimates, currently, North America captures the majority share of the market. However, market share in Asia is anticipated to grow at a higher CAGR during the forecast period.

Example Players in Artificial Intelligence Market

  • Alibaba Cloud
  • AMD
  • Arrow AI
  • AWS
  • Baidu
  • BMI
  • Cisco
  • DeepL
  • Dilapad
  • Glean
  • Google
  • HPE
  • HQE System
  • Huawei
  • Inbenta
  • Intel
  • Meta
  • Microsoft
  • Moveworks
  • NVIDIA
  • OpenAI
  • Oracle
  • Qualcomm
  • Salesforce
  • SAP
  • SAS Institute
  • Siemens
  • Spot AI

ARTIFICIAL INTELLIGENCE MARKET: RESEARCH COVERAGE

The report on the Artificial intelligence market features insights on various sections, including:

  • Market Sizing and Opportunity Analysis: An in-depth analysis of the Artificial intelligence market, focusing on key market segments, including [A] type of offering, [B] type of technology, [C] type of deployment, [D] type of application, [E] type of end user and [F] geographical regions.
  • Competitive Landscape: A comprehensive analysis of the companies engaged in the Artificial intelligence market, based on several relevant parameters, such as [A] year of establishment, [B] company size, [C] location of headquarters, [D] ownership structure.
  • Company Profiles: Elaborate profiles of prominent players engaged in the Artificial intelligence market, providing details on [A] location of headquarters, [B]company size, [C] company mission, [D] company footprint, [E] management team, [F] contact details, [G] financial information, [H] operating business segments, [I] artificial intelligence portfolio, [J] moat analysis, [K] recent developments, and an informed future outlook.
  • SWOT Analysis: An insightful SWOT framework, highlighting the strengths, weaknesses, opportunities and threats in the domain. Additionally, it provides Harvey ball analysis, highlighting the relative impact of each SWOT parameter.

KEY QUESTIONS ANSWERED IN THIS REPORT

  • How many companies are currently engaged in this market?
  • Which are the leading companies in this market?
  • What is the significance of edge AI in the Artificial intelligence market?
  • What factors are likely to influence the evolution of this market?
  • What is the current and future market size?
  • What is the CAGR of this market?
  • How is the current and future market opportunity likely to be distributed across key market segments?
  • Which type of Artificial intelligence is expected to dominate the market?

REASONS TO BUY THIS REPORT

  • The report provides a comprehensive market analysis, offering detailed revenue projections of the overall market and its specific sub-segments. This information is valuable to both established market leaders and emerging entrants.
  • Stakeholders can leverage the report to gain a deeper understanding of the competitive dynamics within the market. By analyzing the competitive landscape, businesses can make informed decisions to optimize their market positioning and develop effective go-to-market strategies.
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TABLE OF CONTENTS

1. PREFACE

  • 1.1. Introduction
  • 1.2. Market Share Insights
  • 1.3. Key Market Insights
  • 1.4. Report Coverage
  • 1.5. Key Questions Answered
  • 1.6. Chapter Outlines

2. RESEARCH METHODOLOGY

  • 2.1. Chapter Overview
  • 2.2. Research Assumptions
  • 2.3. Database Building
    • 2.3.1. Data Collection
    • 2.3.2. Data Validation
    • 2.3.3. Data Analysis
  • 2.4. Project Methodology
    • 2.4.1. Secondary Research
      • 2.4.1.1. Annual Reports
      • 2.4.1.2. Academic Research Papers
      • 2.4.1.3. Company Websites
      • 2.4.1.4. Investor Presentations
      • 2.4.1.5. Regulatory Filings
      • 2.4.1.6. White Papers
      • 2.4.1.7. Industry Publications
      • 2.4.1.8. Conferences and Seminars
      • 2.4.1.9. Government Portals
      • 2.4.1.10. Media and Press Releases
      • 2.4.1.11. Newsletters
      • 2.4.1.12. Industry Databases
      • 2.4.1.13. Roots Proprietary Databases
      • 2.4.1.14. Paid Databases and Sources
      • 2.4.1.15. Social Media Portals
      • 2.4.1.16. Other Secondary Sources
    • 2.4.2. Primary Research
      • 2.4.2.1. Introduction
      • 2.4.2.2. Types
        • 2.4.2.2.1. Qualitative
        • 2.4.2.2.2. Quantitative
      • 2.4.2.3. Advantages
      • 2.4.2.4. Techniques
        • 2.4.2.4.1. Interviews
        • 2.4.2.4.2. Surveys
        • 2.4.2.4.3. Focus Groups
        • 2.4.2.4.4. Observational Research
        • 2.4.2.4.5. Social Media Interactions
      • 2.4.2.5. Stakeholders
        • 2.4.2.5.1. Company Executives (CXOs)
        • 2.4.2.5.2. Board of Directors
        • 2.4.2.5.3. Company Presidents and Vice Presidents
        • 2.4.2.5.4. Key Opinion Leaders
        • 2.4.2.5.5. Research and Development Heads
        • 2.4.2.5.6. Technical Experts
        • 2.4.2.5.7. Subject Matter Experts
        • 2.4.2.5.8. Scientists
        • 2.4.2.5.9. Doctors and Other Healthcare Providers
      • 2.4.2.6. Ethics and Integrity
        • 2.4.2.6.1. Research Ethics
        • 2.4.2.6.2. Data Integrity
    • 2.4.3. Analytical Tools and Databases

3. ECONOMIC AND OTHER PROJECT SPECIFIC CONSIDERATIONS

  • 3.1. Forecast Methodology
    • 3.1.1. Top-Down Approach
    • 3.1.2. Bottom-Up Approach
    • 3.1.3. Hybrid Approach
  • 3.2. Market Assessment Framework
    • 3.2.1. Total Addressable Market (TAM)
    • 3.2.2. Serviceable Addressable Market (SAM)
    • 3.2.3. Serviceable Obtainable Market (SOM)
    • 3.2.4. Currently Acquired Market (CAM)
  • 3.3. Forecasting Tools and Techniques
    • 3.3.1. Qualitative Forecasting
    • 3.3.2. Correlation
    • 3.3.3. Regression
    • 3.3.4. Time Series Analysis
    • 3.3.5. Extrapolation
    • 3.3.6. Convergence
    • 3.3.7. Forecast Error Analysis
    • 3.3.8. Data Visualization
    • 3.3.9. Scenario Planning
    • 3.3.10. Sensitivity Analysis
  • 3.4. Key Considerations
    • 3.4.1. Demographics
    • 3.4.2. Market Access
    • 3.4.3. Reimbursement Scenarios
    • 3.4.4. Industry Consolidation
  • 3.5. Robust Quality Control
  • 3.6. Key Market Segmentations
  • 3.7. Limitations

4. MACRO-ECONOMIC INDICATORS

  • 4.1. Chapter Overview
  • 4.2. Market Dynamics
    • 4.2.1. Time Period
      • 4.2.1.1. Historical Trends
      • 4.2.1.2. Current and Forecasted Estimates
    • 4.2.2. Currency Coverage
      • 4.2.2.1. Overview of Major Currencies Affecting the Market
      • 4.2.2.2. Impact of Currency Fluctuations on the Industry
    • 4.2.3. Foreign Exchange Impact
      • 4.2.3.1. Evaluation of Foreign Exchange Rates and Their Impact on Market
      • 4.2.3.2. Strategies for Mitigating Foreign Exchange Risk
    • 4.2.4. Recession
      • 4.2.4.1. Historical Analysis of Past Recessions and Lessons Learnt
      • 4.2.4.2. Assessment of Current Economic Conditions and Potential Impact on the Market
    • 4.2.5. Inflation
      • 4.2.5.1. Measurement and Analysis of Inflationary Pressures in the Economy
      • 4.2.5.2. Potential Impact of Inflation on the Market Evolution
    • 4.2.6. Interest Rates
      • 4.2.6.1. Overview of Interest Rates and Their Impact on the Market
      • 4.2.6.2. Strategies for Managing Interest Rate Risk
    • 4.2.7. Commodity Flow Analysis
      • 4.2.7.1. Type of Commodity
      • 4.2.7.2. Origins and Destinations
      • 4.2.7.3. Values and Weights
      • 4.2.7.4. Modes of Transportation
    • 4.2.8. Global Trade Dynamics
      • 4.2.8.1. Import Scenario
      • 4.2.8.2. Export Scenario
    • 4.2.9. War Impact Analysis
      • 4.2.9.1. Russian-Ukraine War
      • 4.2.9.2. Israel-Hamas War
    • 4.2.10. COVID Impact / Related Factors
      • 4.2.10.1. Global Economic Impact
      • 4.2.10.2. Industry-specific Impact
      • 4.2.10.3. Government Response and Stimulus Measures
      • 4.2.10.4. Future Outlook and Adaptation Strategies
    • 4.2.11. Other Indicators
      • 4.2.11.1. Fiscal Policy
      • 4.2.11.2. Consumer Spending
      • 4.2.11.3. Gross Domestic Product (GDP)
      • 4.2.11.4. Employment
      • 4.2.11.5. Taxes
      • 4.2.11.6. R&D Innovation
      • 4.2.11.7. Stock Market Performance
      • 4.2.11.8. Supply Chain
      • 4.2.11.9. Cross-Border Dynamics

5. EXECUTIVE SUMMARY

6. INTRODUCTION

  • 6.1. Chapter Overview
  • 6.2. Overview of Artificial Intelligence Market
    • 6.2.1. Type of Offering
    • 6.2.2. Type of Technology
    • 6.2.3. Type of Deployment
    • 6.2.4. Type of Application
    • 6.2.5. Type of End User
  • 6.3. Future Perspective

7. COMPETITIVE LANDSCAPE

  • 7.1. Chapter Overview
  • 7.2. Artificial Intelligence: Overall Market Landscape
    • 7.2.1. Analysis by Year of Establishment
    • 7.2.2. Analysis by Company Size
    • 7.2.3. Analysis by Location of Headquarters
    • 7.2.4. Analysis by Ownership Structure

8. COMPANY PROFILES

  • 8.1. Chapter Overview
  • 8.2. Alibaba Cloud*
    • 8.2.1. Company Overview
    • 8.2.2. Company Mission
    • 8.2.3. Company Footprint
    • 8.2.4. Management Team
    • 8.2.5. Contact Details
    • 8.2.6. Financial Performance
    • 8.2.7. Operating Business Segments
    • 8.2.8. Service / Product Portfolio (project specific)
    • 8.2.9. MOAT Analysis
    • 8.2.10. Recent Developments and Future Outlook
  • 8.3. AMD
  • 8.4. AMD
  • 8.5. Arrow AI
  • 8.6. AWS
  • 8.7. Baidu
  • 8.8. BMI
  • 8.9. Cisco
  • 8.10. DeepL
  • 8.11. Dialpad
  • 8.12. Glean
  • 8.13. Google
  • 8.14. Golden Omega
  • 8.15. HPE
  • 8.16. HQE System
  • 8.17. Koninklijke
  • 8.18. Huawei
  • 8.19. Inbenta
  • 8.20. Intel
  • 8.21. Meta
  • 8.22. Microsoft
  • 8.23. Moveworks
  • 8.24. NVIDIA
  • 8.25. OpenAI
  • 8.26. Oracle
  • 8.27. Qualcomm
  • 8.28. Salesforce
  • 8.29. SAP
  • 8.30. Seimens

9. VALUE CHAIN ANALYSIS

10. SWOT ANALYSIS

11. GLOBAL ARTIFICIAL INTELLIGENCE MARKET

  • 11.1. Chapter Overview
  • 11.2. Key Assumptions and Methodology
  • 11.3. Trends Disruption Impacting Market
  • 11.4. Global Artificial Intelligence Market, Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
  • 11.5. Multivariate Scenario Analysis
    • 11.5.1. Conservative Scenario
    • 11.5.2. Optimistic Scenario
  • 11.6. Key Market Segmentations

12. MARKET OPPORTUNITIES BASED ON TYPE OF OFFERING

  • 12.1. Chapter Overview
  • 12.2. Key Assumptions and Methodology
  • 12.3. Revenue Shift Analysis
  • 12.4. Market Movement Analysis
  • 12.5. Penetration-Growth (P-G) Matrix
  • 12.6. Artificial Intelligence Market for Hardware: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
  • 12.7. Artificial Intelligence Market for Software: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
  • 12.8. Artificial Intelligence Market for Services: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
  • 12.9. Data Triangulation and Validation

13. MARKET OPPORTUNITIES BASED ON TYPE OF TECHNOLOGY

  • 13.1. Chapter Overview
  • 13.2. Key Assumptions and Methodology
  • 13.3. Revenue Shift Analysis
  • 13.4. Market Movement Analysis
  • 13.5. Penetration-Growth (P-G) Matrix
  • 13.6. Artificial Intelligence Market for Computer Vision: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
  • 13.7. Artificial Intelligence Market for Context-Aware AI: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
  • 13.8. Artificial Intelligence Market for Experts Systems: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
  • 13.9. Artificial Intelligence Market for Machine Learning: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
  • 13.10. Artificial Intelligence Market for Natural Language Processing: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
  • 13.11. Artificial Intelligence Market for Robotics Process Automation: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
  • 13.12. Data Triangulation and Validation

14. MARKET OPPORTUNITIES BASED ON TYPE OF DEPLOYMENT

  • 14.1 Chapter Overview
  • 14.2 Key Assumptions and Methodology
  • 14.3. Revenue Shift Analysis
  • 14.4. Market Movement Analysis
  • 14.5. Penetration-Growth (P-G) Matrix
  • 14.6. Artificial Intelligence Market for Cloud-Based: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
  • 14.7. Artificial Intelligence Market for On-Premises: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
  • 14.8. Data Triangulation and Validation

15. MARKET OPPORTUNITIES BASED ON TYPE OF APPLICATION

  • 15.1 Chapter Overview
  • 15.2 Key Assumptions and Methodology
  • 15.3. Revenue Shift Analysis
  • 15.4. Market Movement Analysis
  • 15.5. Penetration-Growth (P-G) Matrix
  • 15.6. Artificial Intelligence Market for Automated Customer Service: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
  • 15.7. Artificial Intelligence Market for Fraud Detection & Risk Management: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
  • 15.8. Artificial Intelligence Market for Healthcare Diagnostics: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
  • 15.9. Artificial Intelligence Market for Marketing & Sales: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
  • 15.10. Artificial Intelligence Market for Predictive Analytics: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
  • 15.11. Artificial Intelligence Market for Robotics: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
  • 15.12. Artificial Intelligence Market for Supply Chain Optimization: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
  • 15.13. Data Triangulation and Validation

16. MARKET OPPORTUNITIES BASED ON TYPE OF END USER

  • 16.1. Chapter Overview
  • 16.2. Key Assumptions and Methodology
  • 16.3. Revenue Shift Analysis
  • 16.4. Market Movement Analysis
  • 16.5. Penetration-Growth (P-G) Matrix
  • 16.6. Artificial Intelligence Market for Automotive: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
  • 16.7. Artificial Intelligence Market for BFSI: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
  • 16.8. Artificial Intelligence Market for Energy & Utilities: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
  • 16.9. Artificial Intelligence Market for Government: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
  • 16.10. Artificial Intelligence Market for Healthcare: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
  • 16.11. Artificial Intelligence Market for Manufacturing: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
  • 16.12. Artificial Intelligence Market for Retail & E-Commerce: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
  • 16.13. Artificial Intelligence Market for Telecommunication: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
  • 16.14. Artificial Intelligence Market for Others: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
  • 16.15. Data Triangulation and Validation

17. MARKET OPPORTUNITIES FOR ARTIFICIAL INTELLIGENCE IN NORTH AMERICA

  • 17.1. Chapter Overview
  • 17.2. Key Assumptions and Methodology
  • 17.3. Revenue Shift Analysis
  • 17.4. Market Movement Analysis
  • 17.5. Penetration-Growth (P-G) Matrix
  • 17.6. Artificial Intelligence Market in North America: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
    • 17.6.1. Artificial Intelligence Market in the US: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
    • 17.6.2. Artificial Intelligence Market in Canada: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
    • 17.6.3. Artificial Intelligence Market in Mexico: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
    • 17.6.4. Artificial Intelligence Market in Other North American Countries: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
  • 17.7. Data Triangulation and Validation

18. MARKET OPPORTUNITIES FOR ARTIFICIAL INTELLIGENCE IN EUROPE

  • 18.1. Chapter Overview
  • 18.2. Key Assumptions and Methodology
  • 18.3. Revenue Shift Analysis
  • 18.4. Market Movement Analysis
  • 18.5. Penetration-Growth (P-G) Matrix
  • 18.6. Artificial Intelligence Market in Europe: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
    • 18.6.1. Artificial Intelligence Market in Austria: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
    • 18.6.2. Artificial Intelligence Market in Belgium: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
    • 18.6.3. Artificial Intelligence Market in Denmark: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
    • 18.6.4. Artificial Intelligence Market in France: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
    • 18.6.5. Artificial Intelligence Market in Germany: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
    • 18.6.6. Artificial Intelligence Market in Ireland: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
    • 18.6.7. Artificial Intelligence Market in Italy: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
    • 18.6.8. Artificial Intelligence Market in Netherlands: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
    • 18.6.9. Artificial Intelligence Market in Norway: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
    • 18.6.10. Artificial Intelligence Market in Russia: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
    • 18.6.11. Artificial Intelligence Market in Spain: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
    • 18.6.12. Artificial Intelligence Market in Sweden: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
    • 18.6.13. Artificial Intelligence Market in Sweden: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
    • 18.6.14. Artificial Intelligence Market in Switzerland: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
    • 18.6.15. Artificial Intelligence Market in the UK: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
    • 18.6.16. Artificial Intelligence Marketing Other European Countries: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
  • 18.7. Data Triangulation and Validation

19. MARKET OPPORTUNITIES FOR ARTIFICIAL INTELLIGENCE IN ASIA

  • 19.1. Chapter Overview
  • 19.2. Key Assumptions and Methodology
  • 19.3. Revenue Shift Analysis
  • 19.4. Market Movement Analysis
  • 19.5. Penetration-Growth (P-G) Matrix
  • 19.6. Artificial Intelligence Market in Asia: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
    • 19.6.1. Artificial Intelligence Market in China: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
    • 19.6.2. Artificial Intelligence Market in India: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
    • 19.6.3. Artificial Intelligence Market in Japan: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
    • 19.6.4. Artificial Intelligence Market in Singapore: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
    • 19.6.5. Artificial Intelligence Market in South Korea: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
    • 19.6.6. Artificial Intelligence Market in Other Asian Countries: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
  • 19.7. Data Triangulation and Validation

20. MARKET OPPORTUNITIES FOR ARTIFICIAL INTELLIGENCE IN MIDDLE EAST AND NORTH AFRICA (MENA)

  • 20.1. Chapter Overview
  • 20.2. Key Assumptions and Methodology
  • 20.3. Revenue Shift Analysis
  • 20.4. Market Movement Analysis
  • 20.5. Penetration-Growth (P-G) Matrix
  • 20.6. Artificial Intelligence Market in Middle East and North Africa (MENA): Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
    • 20.6.1. Artificial Intelligence Market in Egypt: Historical Trends (Since 2019) and Forecasted Estimates (Till 205)
    • 20.6.2. Artificial Intelligence Market in Iran: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
    • 20.6.3. Artificial Intelligence Market in Iraq: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
    • 20.6.4. Artificial Intelligence Market in Israel: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
    • 20.6.5. Artificial Intelligence Market in Kuwait: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
    • 20.6.6. Artificial Intelligence Market in Saudi Arabia: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
    • 20.6.7. Artificial Intelligence Market in United Arab Emirates (UAE): Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
    • 20.6.8. Artificial Intelligence Market in Other MENA Countries: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
  • 20.7. Data Triangulation and Validation

21. MARKET OPPORTUNITIES FOR ARTIFICIAL INTELLIGENCE IN LATIN AMERICA

  • 21.1. Chapter Overview
  • 21.2. Key Assumptions and Methodology
  • 21.3. Revenue Shift Analysis
  • 21.4. Market Movement Analysis
  • 21.5. Penetration-Growth (P-G) Matrix
  • 21.6. Artificial Intelligence Market in Latin America: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
    • 21.6.1. Artificial Intelligence Market in Argentina: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
    • 21.6.2. Artificial Intelligence Market in Brazil: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
    • 21.6.3. Artificial Intelligence Market in Chile: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
    • 21.6.4. Artificial Intelligence Market in Colombia Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
    • 21.6.5. Artificial Intelligence Market in Venezuela: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
    • 21.6.6. Artificial Intelligence Market in Other Latin American Countries: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
  • 21.7. Data Triangulation and Validation

22. MARKET OPPORTUNITIES FOR ARTIFICIAL INTELLIGENCE IN REST OF THE WORLD

  • 22.1. Chapter Overview
  • 22.2. Key Assumptions and Methodology
  • 22.3. Revenue Shift Analysis
  • 22.4. Market Movement Analysis
  • 22.5. Penetration-Growth (P-G) Matrix
  • 22.6. Artificial Intelligence Market in Rest of the World: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
    • 22.6.1. Artificial Intelligence Market in Australia: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
    • 22.6.2. Artificial Intelligence Market in New Zealand: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
    • 22.6.3. Artificial Intelligence Market in Other Countries
  • 22.7. Data Triangulation and Validation

23. TABULATED DATA

24. LIST OF COMPANIES AND ORGANIZATIONS

25. CUSTOMIZATION OPPORTUNITIES

26. ROOTS SUBSCRIPTION SERVICES

27. AUTHOR DETAIL