查看购物车
  • Traditional Chinese
  • English
  • Japanese
封面
市场调查报告书
商品编码
1737239

2026 年至 2032 年人工智慧 (AI) 软体市场（按组件、部署类型、公司规模和地区划分）

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
出版日期: | 出版商: Verified Market Research | 英文 202 Pages | 商品交期: 2-3个工作天内

价格
简介目录

人工智慧（AI）软体市场评估-2026-2032

人工智慧 (AI) 软体的需求日益增长，源自于其在各行各业提升业务效率、决策能力和消费者体验方面的颠覆性潜力。 AI 软体能够自动执行复杂业务，提供预测分析，并支援即时数据处理——所有这些对于寻求提升绩效和获得竞争优势的企业都至关重要。预计到 2024 年，AI 软体的收入将超过 5,153.1 亿美元，到 2032 年，其估值将达到约 2,7404.6 亿美元。

巨量资料、云端运算和物联网 (IoT) 的兴起，推动了对能够处理大量资讯并提取有用洞察的人工智慧软体的需求。越来越多的企业开始利用人工智慧进行数据主导的决策，这在当今快节奏的数位环境中至关重要。人工智慧能够评估趋势、预测市场动向并改善产品供应，使其成为商务策略中的关键要素，并推动市场在 2026 年至 2032 年期间的复合年增长率达到 20.4%。

人工智慧（AI）软体市场：定义/概述

人工智慧 (AI) 软体是一种模拟人类智慧并执行认知过程（例如学习、推理、解决问题、感知和自然语言理解）的电脑程式。 AI 软体使用复杂的演算法和机器学习模型来处理大量资料、发现模式并基于这些资讯做出决策或预测。

人工智慧 (AI) 软体正广泛应用于各行各业，深刻改变企业营运和与客户互动的方式。在医疗保健领域，AI 正被用于预测分析，透过评估大量患者数据来帮助诊断疾病并制定治疗方案。

机器学习、深度学习和神经网路的持续进步可能会大幅提升人工智慧软体的使用率。随着人工智慧的发展，其应用将变得更加复杂，从而实现更高的自动化和个人化。在无人驾驶汽车等领域，人工智慧将改进安全功能和导航系统，使自动驾驶技术更接近现实。

金融领域越来越多地采用人工智慧 (AI) 是否会推动市场成长？

银行业日益广泛地使用人工智慧 (AI)，这是人工智慧软体市场发展的关键驱动力。金融机构利用人工智慧来提升业务效率、客户体验和风险管理。这一趋势源自于各金融服务领域对人工智慧技术的大规模投资和广泛应用。世界经济论坛预测，到 2023 年，85% 的金融机构将实施某种形式的人工智慧，77% 的金融机构预计人工智慧将在两年内成为业务不可或缺的一部分。

人工智慧正在对各种金融服务产生巨大影响。美国证券交易委员会的数据显示，基于人工智慧的交易演算法目前占美国股市总交易量的70%以上。美国国家保险委员会的报告显示，人工智慧的引入已将索赔处理时间缩短了40%。国际货币基金组织预测，到2030年，人工智慧将取代金融业26%的工作时间，在全球节省5,120亿美元的成本。

决策透明度问题会阻碍人工智慧 (AI) 市场的成长吗？

决策透明度问题可能会影响人工智慧 (AI) 领域。人工智慧系统，尤其是基于深度学习等先进机器学习技术的系统，通常如同「黑盒子」一样运作，无法理解它们如何得出特定结果。这种缺乏开放性的情况可能会引发一些担忧。如果无法深入了解人工智慧的决策流程，就很难信任和检验这些结果，尤其是在医疗保健、金融和法律等关键产业。相关人员必须了解人工智慧决策背后的原因，以确保公平、准确和合规。

透明度问题可能会引发伦理担忧，例如人工智慧系统中的偏见可能导致某些群体受到不公平对待。解决此类偏见需要了解决策的製定过程，而缺乏透明度使这一过程变得更加复杂。监管机构越来越多地要求人工智慧系统解释其行为，以确保课责和道德的使用。未能满足这些要求可能会因监管处罚而限制人工智慧的采用。

目录

第一章 全球人工智慧（AI）软体市场简介

  • 市场概览
  • 研究范围
  • 先决条件

第二章执行摘要

第三章：已验证的市场研究调查方法

  • 资料探勘
  • 验证
  • 第一手资料
  • 资料来源列表

第四章 全球人工智慧（AI）软体市场展望

  • 概述
  • 市场动态
    • 驱动程式
    • 限制因素
    • 机会
  • 波特五力模型
  • 价值链分析

第五章全球人工智慧（AI）软体市场（按组件）

  • 概述
  • 软体
  • 服务

第六章全球人工智慧（AI）软体市场按部署类型

  • 概述
  • 本地
  • 云端基础

第七章全球人工智慧（AI）软体市场（依公司规模）

  • 概述
  • 中小企业
  • 大公司

第八章全球人工智慧（AI）软体市场（按地区）

  • 概述
  • 北美洲
    • 美国
    • 加拿大
    • 墨西哥
  • 欧洲
    • 德国
    • 英国
    • 法国
    • 其他欧洲国家
  • 亚太地区
    • 中国
    • 日本
    • 印度
    • 其他亚太地区
  • 世界其他地区
  • 拉丁美洲
  • 中东和非洲

第九章全球人工智慧（AI）软体市场的竞争格局

  • 概述
  • 各公司市场排名
  • 主要发展策略

第十章 公司简介

  • 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

第十一章 附录

  • 相关调查
简介目录
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