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人工知能（AI）ソフトウェア市場：コンポーネント別、展開形態別、企業規模別、地域別、2026-2032年

Artificial Intelligence (AI) Software Market By Component (Software, Services), Deployment Mode (On-Premises, Cloud-Based), Enterprise Size (Small and Medium-sized Enterprises (SMEs), Large Enterprises), & Region for 2026-2032

出版日
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英文 202 Pages
納期
2～3営業日
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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=144.76円
人工知能（AI）ソフトウェア市場：コンポーネント別、展開形態別、企業規模別、地域別、2026-2032年
出版日: 2025年05月09日
発行: Verified Market Research
ページ情報: 英文 202 Pages
納期: 2～3営業日
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概要

人工知能（AI）ソフトウェア市場評価-2026-2032

人工知能（AI）ソフトウェアのニーズが高まっているのは、業務効率、意思決定、消費者体験を向上させる、業界を横断する破壊的な可能性に起因しています。AIソフトウェアは、複雑な業務を自動化し、予測分析を提供し、リアルタイムのデータ処理を可能にします。これらはすべて、業績を向上させ、競争力を高めようとする企業にとって重要であり、2024年には5,153億1,000万米ドルの売上高を突破し、2032年には約2兆7,404億6,000万米ドルの評価額に達します。

ビッグデータ、クラウドコンピューティング、モノのインターネット（IoT）の台頭により、大量の情報を処理して有用な知見を抽出できるAIソフトウェアの需要が高まっています。組織はデータ主導の意思決定のためにAIを利用することが増えており、これは今日のペースの速いデジタル環境では非常に重要です。動向を評価し、市場の動きを予測し、製品の提供を改善するAIの能力は、2026年から2032年までのCAGR 20.4%での市場の成長を可能にすることで、ビジネス戦略においてAIを極めて重要なものにしています。

人工知能（AI）ソフトウェア市場：定義/概要

人工知能（AI）ソフトウェアは、人間の知性をシミュレートし、学習、推論、問題解決、知覚、自然言語理解などの認知プロセスを実行するコンピュータプログラムの一種です。AIソフトウェアは、複雑なアルゴリズムと機械学習モデルを使用して、大量のデータを処理し、パターンを発見し、その情報に基づいて判断や予測を行う。

人工知能（AI）ソフトウェアは業界を問わず様々な用途に使用されており、ビジネスの運営方法や顧客との関わり方を大きく変えています。ヘルスケアでは、AIは予測分析に活用されており、患者データの大規模なデータセットを評価することで、病気の診断や治療計画の立案に役立っています。

機械学習、ディープラーニング、ニューラルネットワークの継続的な進歩により、AIソフトウェアの使用は劇的に増加する可能性が高いです。AIが進歩するにつれて、その用途はより複雑になり、自動化やパーソナライゼーションの拡大が可能になります。ドライバーレス自動車などの分野では、AIによって安全機能やナビゲーション・システムが改善され、自動運転技術がより現実的なものになると思われます。

金融セクターにおける人工知能（AI）の採用増加は市場成長を促進するか？

銀行セクターにおける人工知能（AI）の利用の拡大は、AIソフトウェア市場の主要な促進要因であり、金融機関はAIを利用して業務効率、顧客体験、リスク管理を改善しています。この動向は、大規模な投資と様々な金融サービスにおけるAI技術の広範な採用によって後押しされています。世界経済フォーラムによると、2023年までに金融機関の85%が何らかの形でAIを導入しており、77%が2年以内にAIが業務に不可欠になると予想しています。

AIが様々な金融サービスに与える影響は大きいです。証券取引委員会によると、AIを活用した取引アルゴリズムは現在、米国株式市場における総取引量の70％以上を占めています。全米保険委員会は、AIの導入により保険金請求処理時間が40％短縮されたと報告しています。国際通貨基金によると、AIは2030年までに金融業界の労働時間の26％を代替し、全世界で5,120億米ドルのコストを削減する可能性があるといいます。

意思決定における透明性の問題が人工知能（AI）市場の成長を阻害する可能性は？

意思決定における透明性の問題は、人工知能（AI）分野に影響を与える可能性があります。AIシステム、特にディープラーニングのような高度な機械学習技術に基づくシステムは、「ブラックボックス」として機能することが多く、特定の結果にどのように到達するのかを理解することができないです。このオープン性の欠如は、いくつかの懸念を引き起こす可能性があります。AIの意思決定プロセスに関する具体的な洞察がなければ、特にヘルスケア、金融、法律などの重要な業界において、これらの知見を信頼し検証することは難しいです。利害関係者は、公平性、正確性、規制遵守を確保するために、AIによる判断の根底にある理由を理解しなければならないです。

透明性の問題は、一部の集団に対する不当な扱いをもたらすかもしれないAIシステムのバイアスなど、倫理的な懸念をもたらすかもしれないです。このようなバイアスに対処するには、透明性の欠如によって複雑になる意思決定の方法を理解する必要があります。規制機関は、説明責任と倫理的な使用を保証するために、AIシステムがその行動を説明することをますます要求しています。これらの要件を満たさない場合、規制当局の罰則によりAIの導入が制限される可能性があります。

目次

第1章 世界の人工知能（AI）ソフトウェア市場の導入

  • 市場概要
  • 調査範囲
  • 前提条件

第2章 エグゼクティブサマリー

第3章 VERIFIED MARKET RESEARCHの調査手法

  • データマイニング
  • バリデーション
  • 一次資料
  • データソース一覧

第4章 人工知能（AI）ソフトウェアの世界市場展望

  • 概要
  • 市場力学
    • 促進要因
    • 抑制要因
    • 機会
  • ポーターのファイブフォースモデル
  • バリューチェーン分析

第5章 人工知能（AI）ソフトウェアの世界市場：コンポーネント別

  • 概要
  • ソフトウェア
  • サービス

第6章 人工知能（AI）ソフトウェアの世界市場：展開形態別

  • 概要
  • オンプレミス
  • クラウドベース

第7章 人工知能（AI）ソフトウェアの世界市場：企業規模別

  • 概要
  • 中小企業（SMEs）
  • 大企業

第8章 人工知能（AI）ソフトウェアの世界市場：地域別

  • 概要
  • 北米
    • 米国
    • カナダ
    • メキシコ
  • 欧州
    • ドイツ
    • 英国
    • フランス
    • その他欧州
  • アジア太平洋
    • 中国
    • 日本
    • インド
    • その他アジア太平洋地域
  • 世界のその他の地域
  • ラテンアメリカ
  • 中東・アフリカ

第9章 世界の人工知能（AI）ソフトウェア市場の競合情勢

  • 概要
  • 各社の市場ランキング
  • 主な発展戦略

第10章 企業プロファイル

  • Advanced Micro Devices
  • Overview
  • Financial Performance
  • Product Outlook
  • Key Developments
  • AiCure
  • Overview
  • Financial Performance
  • Product Outlook
  • Key Developments
  • Atomwise, Inc.
  • Overview
  • Financial Performance
  • Product Outlook
  • Key Developments
  • Ayasdi AI LLC
  • Overview
  • Financial Performance
  • Product Outlook
  • Key Developments
  • Baidu, Inc.
  • Overview
  • Financial Performance
  • Product Outlook
  • Key Developments
  • Clarifai, Inc.
  • Overview
  • Financial Performance
  • Product Outlook
  • Key Developments
  • Cyrcadia Health
  • Overview
  • Financial Performance
  • Product Outlook
  • Key Developments
  • Enlitic, Inc.
  • Overview
  • Financial Performance
  • Product Outlook
  • Key Developments
  • Google LLC
  • Overview
  • Financial Performance
  • Product Outlook
  • Key Developments
  • ai.
  • Overview
  • Financial Performance
  • Product Outlook
  • Key Developments
  • HyperVerge, Inc.
  • Overview
  • Financial Performance
  • Product Outlook
  • Key Developments
  • International Business Machines Corporation
  • Overview
  • Financial Performance
  • Product Outlook
  • Key Developments

第11章 付録

  • 関連調査
目次
Product Code: 59091

Artificial Intelligence (AI) Software Market Valuation - 2026-2032

The growing need for Artificial Intelligence (AI) software stems from its disruptive potential across industries which improves operational efficiency, decision-making, and consumer experience. AI software automates complicated operations provides predictive analytics, and allows for real-time data processing all of which are critical for businesses looking to improve performance and compete by enabling the market to surpass a revenue of USD 515.31 Billion valued in 2024 and reach a valuation of around USD 2740.46 Billion by 2032.

The rise of big data, cloud computing, and the Internet of Things (IoT) has increased the demand for AI software that can handle massive amounts of information and extract useful insights. Organizations are increasingly using AI for data-driven decision-making which is critical in today's fast-paced digital landscape. AI's capacity to evaluate trends, predict market movements, and improve product offers has made it crucial in business strategy by enabling the market to grow at a CAGR of 20.4% from 2026 to 2032.

Artificial Intelligence (AI) Software Market: Definition/ Overview

Artificial intelligence (AI) software is a type of computer program that simulates human intellect and performs cognitive processes like learning, reasoning, problem-solving, perception, and natural language understanding. AI software uses complex algorithms and machine learning models to process massive volumes of data, discover patterns, and make judgments or predictions based on that information.

Artificial intelligence (AI) software has several uses across industries, profoundly changing how businesses run and engage with customers. In healthcare, AI is utilized for predictive analytics, which helps with disease diagnosis and treatment planning by evaluating large datasets of patient data.

The use of AI software is likely to grow dramatically, thanks to continued advances in machine learning, deep learning, and neural networks. As AI advances, its applications will grow more complex, enabling increased automation and personalization. In areas such as driverless vehicles, AI will improve safety features and navigation systems making self-driving technology more viable.

Will the Increasing Adoption of Artificial Intelligence (AI) in the Finance Sector Drive Market Growth?

The growing use of Artificial Intelligence (AI) in the banking sector is a primary driver of the AI software market with financial institutions using AI to improve operational efficiency, client experiences, and risk management. This trend is fueled by significant investments and the widespread adoption of AI technologies across a variety of financial services. According to the World Economic Forum, 85% of financial institutions have deployed AI in some capacity by 2023 with 77% expecting AI to become critical to their operations within two years.

The impact of AI on various financial services is significant. According to the Securities and Exchange Commission, AI-powered trading algorithms currently account for more than 70% of total trading volume in the United States equities markets. The National Association of Insurance Commissioners reports that AI implementation has resulted in a 40% reduction in claims processing time. According to the International Monetary Fund, AI has the potential to displace 26% of work hours in the financial industry by 2030, saving USD 512 Billion in worldwide costs.

Could Transparency Issues in Decision-Making Hinder the Growth of the Artificial Intelligence (AI) Market?

Transparency difficulties in decision-making could affect the artificial intelligence (AI) sector. AI systems, particularly those based on advanced machine learning techniques like deep learning, frequently function as "black boxes," making it impossible to understand how they arrive at specific results. This lack of openness may raise several concerns. Without specific insights into AI decision-making processes, it is difficult to trust and validate these findings, especially in critical industries such as healthcare, finance, and law. Stakeholders must understand the reasoning underlying AI-driven judgments to ensure fairness, accuracy, and regulatory adherence.

Transparency issues may pose ethical concerns such as biases in AI systems which might result in unfair treatment of some populations. Addressing these biases necessitates understanding how decisions are made which is complicated by a lack of transparency. Regulatory bodies are increasingly demanding that AI systems explain their actions to ensure accountability and ethical use. Failure to meet these requirements may result in regulatory penalties that limit AI deployment.

Category-Wise Acumens

Will the Growth in Computing Power and Data Availability Drive the Component Segment?

Increasing computing power and data availability will dominate the artificial intelligence (AI) sector, particularly its software component. AI algorithms can be executed quicker and on a wider scale when computing power improves with the introduction of more powerful processors, graphics processing units (GPUs), and specialized AI hardware accelerators such as tensor processors. This increased computer power enables the development and deployment of more complex AI models such as deep learning neural networks which need enormous computational resources.

Furthermore, AI algorithms are powered by massive amounts of data generated by a number of sources such as sensors, IoT devices, social media, and digital platforms. Increased data availability allows AI models to be trained on larger, more diverse datasets, resulting in more accurate and resilient AI applications. Furthermore, advancements in data storage technologies, cloud computing, and edge computing infrastructure have made it easier to store and analyze massive volumes of data enabling AI software to extract important insights and make real-time decisions.

Will the Growing Demand for Easier Access to Advanced AI Capabilities Propel The Deployment Segment?

The increased demand for easy access to advanced AI capabilities will dominate the deployment segment of the artificial intelligence (AI) market, particularly cloud-based solutions. Businesses are quickly recognizing the value of AI in driving innovation, increasing efficiency, and gaining a competitive advantage. Traditional on-premises installations may need significant upfront investments in infrastructure, technical skills, and upkeep making adoption challenging for many businesses. Cloud platforms offer scalable computing resources, pre-configured AI services, and managed infrastructure allowing enterprises to quickly adopt and grow AI solutions based on their specific needs.

Furthermore, cloud-based AI solutions enable businesses to leverage the most recent developments in AI technologies such as machine learning, natural language processing, and computer vision without the need to manage complex infrastructure or software updates. This agility and flexibility enables businesses to experiment with AI, iterate on solutions, and innovate swiftly in response to changing business issues and opportunities. As a result, the growing need for easier access to advanced AI capabilities will drive the development of cloud-based deployment methods influencing the future of the AI sector.

Country/Region-wise Acumens

Will the Growing Adoption of Robust AI Development Environments Drive Growth in the North American Region?

The North American AI software industry is primarily driven by the increasing usage of powerful AI development environments with the United States at the forefront. This dominance is due to the region's superior technological infrastructure, significant investments in R&D, and a thriving ecosystem of tech giants and entrepreneurs. The adoption of AI development environments in North America is indicated by the National Science Foundation's (NSF) claim that US federal funding for AI research and development reached USD 1.9 Billion in fiscal year 2023, a 30% increase over the previous year.

Another important factor driving AI adoption is the corporate sector. According to a poll conducted by the MIT Sloan Management Review, 97% of large organizations in North America are engaging in AI programs with 64% reporting measurable benefits. According to the National Center for Science and Engineering Statistics, corporate enterprise expenditure on AI R&D in the United States would reach USD 78 Billion in 2023, up 15% from the previous year. The use of cloud-based AI platforms is rising, with the US Government Accountability Office forecasting a 25% rise in federal agencies' spending on cloud services, including AI platforms, in 2023 compared to 2022.

Will the Asia Pacific Region Be Driven By Rapid Economic Development and Technological Adoption?

The Asia Pacific region is witnessing the highest growth in the artificial intelligence (AI) software industry owing to rapid economic expansion and increased technological usage. This rapid rise is being driven by significant investments in digital infrastructure, a thriving startup culture, and strong government backing for AI programs across all sectors. Asia Pacific's strong economic growth is a key driver of the AI software market. According to the Asian Development Bank (ADB), the region's GDP increased by 4.8% in 2023, exceeding worldwide norms.

Government initiatives play a critical role in driving AI software adoption. China's New Generation Artificial Intelligence Development Plan aims to position the country as a global leader in AI by 2030, with the Ministry of Science and Technology reporting a USD 2.1 Billion investment in AI research in 2023. Similarly, India's National Strategy for Artificial Intelligence set out $477 million for AI development in the 2023-24 budget. According to the Japan Patent Office, the Society 5.0 project which focuses on integrating AI into all sectors of society, has resulted in a 28% rise in AI-related patents by 2023.

Competitive Landscape

The Artificial Intelligence (AI) Software Market is a dynamic and competitive space, characterized by a diverse range of players vying for market share. These players are on the run for solidifying their presence through the adoption of strategic plans such as collaborations, mergers, acquisitions, and political support. The organizations are focusing on innovating their product line to serve the vast population in diverse regions.

Some of the prominent players operating in the artificial intelligence (AI) software market include:

  • Advanced Micro Devices
  • AiCure
  • Arm Limited
  • Atomwise, Inc.
  • Ayasdi AI LLC
  • Baidu, Inc.
  • Clarifai, Inc.
  • Cyrcadia Health
  • Enlitic, Inc.
  • Google LLC
  • ai.
  • HyperVerge, Inc.
  • International Business Machines Corporation

Latest Developments

  • In March 2024, Microsoft and NVIDIA announced a collaboration focused on advancing AI for the healthcare and life sciences industry. This partnership leverages the strengths of both companies: Microsoft Azure's cloud infrastructure and advanced computing capabilities, alongside NVIDIA's DGX Cloud and Clara suite. The goal is to accelerate innovation and improve patient care through developments in areas like clinical research and drug discovery.
  • In March 2024, NVIDIA launched new Generative AI Microservices designed to advance medical technology (MedTech), drug discovery, and digital health. These microservices leverage artificial intelligence (AI) to potentially improve healthcare technology.

Artificial Intelligence (AI) Software Market, By Category

  • Component:
  • Software
  • Services
  • Deployment Mode:
  • On-Premises
  • Cloud-Based
  • Enterprise Size:
  • Small and Medium-sized Enterprises (SMEs)
  • Large Enterprises
  • Region:
  • North America
  • Europe
  • Asia-Pacific
  • South America
  • Middle East & Africa

TABLE OF CONTENTS

1 INTRODUCTION OF GLOBAL ARTIFICIAL INTELLIGENCE (AI) SOFTWARE MARKET

  • 1.1 Overview of the Market
  • 1.2 Scope of Report
  • 1.3 Assumptions

2 EXECUTIVE SUMMARY

3 RESEARCH METHODOLOGY OF VERIFIED MARKET RESEARCH

  • 3.1 Data Mining
  • 3.2 Validation
  • 3.3 Primary Interviews
  • 3.4 List of Data Sources

4 GLOBAL ARTIFICIAL INTELLIGENCE (AI) SOFTWARE MARKET OUTLOOK

  • 4.1 Overview
  • 4.2 Market Dynamics
    • 4.2.1 Drivers
    • 4.2.2 Restraints
    • 4.2.3 Opportunities
  • 4.3 Porters Five Force Model
  • 4.4 Value Chain Analysis

5 GLOBAL ARTIFICIAL INTELLIGENCE (AI) SOFTWARE MARKET, BY COMPONENT

  • 5.1 Overview
  • 5.2 Software
  • 5.3 Services

6 GLOBAL ARTIFICIAL INTELLIGENCE (AI) SOFTWARE MARKET, BY DEPLOYMENT MODE

  • 6.1 Overview
  • 6.2 On-Premises
  • 6.3 Cloud-Based

7 GLOBAL ARTIFICIAL INTELLIGENCE (AI) SOFTWARE MARKET, BY ENTERPRISE SIZE

  • 7.1 Overview
  • 7.2 Small and Medium-sized Enterprises (SMEs)
  • 7.3 Large Enterprises

8 GLOBAL ARTIFICIAL INTELLIGENCE (AI) SOFTWARE MARKET, BY GEOGRAPHY

  • 8.1 Overview
  • 8.2 North America
    • 8.2.1 U.S.
    • 8.2.2 Canada
    • 8.2.3 Mexico
  • 8.3 Europe
    • 8.3.1 Germany
    • 8.3.2 U.K.
    • 8.3.3 France
    • 8.3.4 Rest of Europe
  • 8.4 Asia Pacific
    • 8.4.1 China
    • 8.4.2 Japan
    • 8.4.3 India
    • 8.4.4 Rest of Asia Pacific
  • 8.5 Rest of the World
  • 8.6 Latin America
  • 8.7 Middle East and Africa

9 GLOBAL ARTIFICIAL INTELLIGENCE (AI) SOFTWARE MARKET COMPETITIVE LANDSCAPE

  • 9.1 Overview
  • 9.2 Company Market Ranking
  • 9.3 Key Development Strategies

10 COMPANY PROFILES

  • 10.1 Advanced Micro Devices
  • Overview
  • Financial Performance
  • Product Outlook
  • Key Developments
  • 10.2 AiCure
  • Overview
  • Financial Performance
  • Product Outlook
  • Key Developments
  • 10.3 Atomwise, Inc.
  • Overview
  • Financial Performance
  • Product Outlook
  • Key Developments
  • 10.4 Ayasdi AI LLC
  • Overview
  • Financial Performance
  • Product Outlook
  • Key Developments
  • 10.5 Baidu, Inc.
  • Overview
  • Financial Performance
  • Product Outlook
  • Key Developments
  • 10.6 Clarifai, Inc.
  • Overview
  • Financial Performance
  • Product Outlook
  • Key Developments
  • 10.7 Cyrcadia Health
  • Overview
  • Financial Performance
  • Product Outlook
  • Key Developments
  • 10.8 Enlitic, Inc.
  • Overview
  • Financial Performance
  • Product Outlook
  • Key Developments
  • 10.9 Google LLC
  • Overview
  • Financial Performance
  • Product Outlook
  • Key Developments
  • 10.10 ai.
  • Overview
  • Financial Performance
  • Product Outlook
  • Key Developments
  • 10.11 HyperVerge, Inc.
  • Overview
  • Financial Performance
  • Product Outlook
  • Key Developments
  • 10.12 International Business Machines Corporation
  • Overview
  • Financial Performance
  • Product Outlook
  • Key Developments

11 Appendix

  • 11.1 Related Research