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市场调查报告书
商品编码
1574124

人工智慧工程市场：2024-2029 年预测

Artificial Intelligence Engineering Market - Forecasts from 2024 to 2029
出版日期: | 出版商: Knowledge Sourcing Intelligence | 英文 145 Pages | 商品交期: 最快1-2个工作天内

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简介目录

人工智慧工程市场预计将从 2024 年的 109.04 亿美元增至 2029 年的 480.74 亿美元，预测期内复合年增长率为 34.54%。

人工智慧工程是一个跨学科领域，它定制和整合电脑科学概念和资讯技术基础设施，以开发新的人工智慧软体解决方案和工具，可应用于现实世界中的各种行业。人工智慧工程师根据目标客户和产业需求，利用深度学习概念、机器学习模型、自然语言处理能力、神经网路系统演算法、电脑视觉技术等开发各种人工智慧产品。

此外，由于人工智慧技术具有众多优势，汽车、医疗保健、零售、通讯和製造等各行业的公司正在将基于人工智慧的软体、硬体和服务纳入其业务运营。因此，在预测期内，人工智慧技术的广泛接受以及大多数经济领域对人工智慧驱动的技术解决方案的需求不断增加，可能会推动人工智慧工程市场的进一步扩张。

人工智慧工程市场的驱动因素：

  • 对业务自动化的需求不断增长预计将推动市场成长。

最大限度地提高业务任务的业务并透过减少人为错误来提高准确性水平正在推动业务。根据IBM 2023年发布的《IBM全球人工智慧采用指数》，大约42%的企业级组织正在业务中使用人工智慧，59%的企业计划儘早利用人工智慧并扩大投资。最积极使用人工智慧的行业是金融服务和通讯，金融服务领域近一半的 IT 专业人员表示在其公司中实施了人工智慧，而通讯业的 IT 专家也报告了类似比例 (37%)。

因此，对业务自动化的需求不断增长以及各行业对人工智慧技术的采用正在推动人工智慧工程市场的发展。例如，2024 年 4 月，微软和 Iprova 合作主办了人工智慧辅助发明高峰会。本次高峰会旨在共用人工智慧辅助发明的现实经验、挑战和未解决的问题。本次研讨会面向技术专家、相关人员以及人工智慧辅助发明的现有和未来的新用户，以深入研究可能已经饱和状态的领域。

人工智慧工程市场地域展望：

  • 北美地区预计将占据人工智慧工程市场的重要份额。

主要企业和品牌逐渐转向数位化，正在推动业务营运和其他相关活动的自动化。因此，对人工智慧产品的需求不断增加。 Google、亚马逊等国际科技巨头的出现，以及近年来美国Cruise Automation、Palantir Technologies、Tempus Labs等新型人工智慧软体新兴企业的出现，进一步增加了北美人工智慧工程的市场机会正在生产。

此外，Veritone还分析了美国劳工统计局的就业报告，以了解该国的人工智慧招募趋势。根据 Aspen Tech Labs 的就业市场脉搏的分析，与 BLS 的统计数据相比，国内人工智慧职缺增加了 32%，根据我们的即时资料库，该数据汇总了来自 112,000 名雇主的超过 500 万个美国职位空缺。因此，北美人工智慧工程市场预计在预测期内将大幅扩张。

为什么要购买这份报告？

  • 洞察分析：深入洞察关键和新兴地区的市场，重点关注客户细分、政府政策、社会经济因素、消费者偏好、产业和其他子区隔。
  • 竞争格局：了解世界各地主要企业采取的策略策略，并了解采用正确策略渗透市场的潜力。
  • 市场驱动因素和未来趋势：检视动态因素和关键市场趋势，并探讨它们将如何影响未来的市场发展。
  • 可行的建议：利用洞察力做出策略决策，在动态环境中发现新的业务流和收益。
  • 迎合广泛的受众：对于新兴企业、研究机构、顾问、中小型企业和大型企业来说有用且具有成本效益。

公司使用我们的报告的目的是什么？

产业和市场考量、机会评估、产品需求预测、打入市场策略、地理扩张、资本投资决策、法律规范与影响、新产品开拓、竞争影响

调查范围

  • 过去的资料/预测，2022-2029
  • 成长机会、挑战、供应链前景、法规结构、顾客行为、趋势分析
  • 竞争定位、策略和市场占有率分析
  • 区域收益成长和预测分析，包括细分市场和国家
  • 公司概况（策略、产品、财务资讯、主要发展等）

目录

第一章简介

  • 市场概况
  • 市场定义
  • 调查范围
  • 市场区隔
  • 货币
  • 先决条件
  • 基准年和预测年时间表
  • 相关人员的主要利益

第二章调查方法

  • 研究设计
  • 调查过程

第三章执行摘要

  • 主要发现

第四章市场动态

  • 市场驱动因素
  • 市场限制因素
  • 波特五力分析
  • 产业价值链分析
  • 分析师观点

第五章 人工智慧工程市场：依技术分类

  • 介绍
  • 深度学习
  • 机器学习
  • 自然语言处理
  • 电脑视觉

第六章 人工智慧工程市场：依发展划分

  • 介绍
  • 云
  • 本地

第七章 人工智慧工程市场：按解决方案

  • 介绍
  • 软体
  • 服务
  • 硬体

第八章人工智慧工程市场：依最终用户分类

  • 介绍
  • 车
  • 沟通
  • 製造业
  • 卫生保健
  • 其他的

第九章 人工智慧工程市场：按地区

  • 介绍
  • 北美洲
    • 依技术
    • 按发展
    • 按解决方案
    • 按最终用户
    • 按国家/地区
  • 南美洲
    • 依技术
    • 按发展
    • 按解决方案
    • 按最终用户
    • 按国家/地区
  • 欧洲
    • 依技术
    • 按发展
    • 按解决方案
    • 按最终用户
    • 按国家/地区
  • 中东/非洲
    • 依技术
    • 按发展
    • 按解决方案
    • 按最终用户
    • 按国家/地区
  • 亚太地区
    • 依技术
    • 按发展
    • 按解决方案
    • 按最终用户
    • 按国家/地区

第十章竞争环境及分析

  • 主要企业及策略分析
  • 市场占有率分析
  • 合併、收购、协议和合作
  • 竞争对手仪表板

第十一章 公司简介

  • Intel Corporation
  • Microsoft Corporation
  • Oracle Corporation
  • IBM Corporation
  • NVIDIA Corporation
  • People.ai Inc
  • Cisco Systems
  • Verint Systems
  • Salesforce
  • Siemens AG
简介目录
Product Code: KSI061614836

The artificial intelligence engineering market is projected to witness a CAGR of 34.54% during the forecast period to reach a total market size of US$48.074 billion by 2029, up from US$10.904 billion in 2024.

Artificial intelligence engineering is an interdisciplinary field that customizes and integrates computer science concepts and information technology infrastructure to develop new software solutions and tools of artificial intelligence that can be applied across various industries in a real-world context. As per the requirements of their target client or industry, AI engineers develop diversified AI products using deep learning concepts, machine learning models, natural language processing abilities, neural networking system algorithms, and computer vision technology.

Furthermore, companies in different industries, such as automotive, healthcare, retail, communications, and manufacturing, are integrating AI-based software, hardware, and services into their business operations due to the numerous benefits associated with AI technology. Hence, the extensive embracement of AI technology and the increase in demand for AI-powered technological solutions across the majority of an economy's sectors will encourage the further expansion of the artificial intelligence engineering market during the forecast period.

ARTIFICIAL INTELLIGENCE ENGINEERING MARKET DRIVERS:

  • The increasing requirement for business automation is anticipated to drive the market growth.

The maximization of operational productivity of business tasks and the enhancement in accuracy levels due to the reduction in human errors are promoting the automation of business operations. The IBM Global AI Adoption Index released by IBM in 2023 established that approximately 42% of enterprise-level organizations have AI in operation for their business, while 59% utilize AI and plan to extend investment at an early stage. Financial services and telecommunications businesses are the most AI-active industries, with about half of IT professionals reporting deployment of AI in their companies in the financial service industry and a similar percentage for the telecommunication sector, which is 37% of IT experts report the same.

Therefore, the increasing demand for business automation and the adoption of AI technology by various industries are propelling the artificial intelligence engineering market. For instance, in April 2024, Microsoft and Iprova teamed up to organize the AI-Assisted Invention Summit, a conference dedicated to sharing experiences of what works in AI-assisted invention in practice, as well as challenges and open issues. This symposium aimed to cater to technology experts, academics, and existing and budding future users of AI-assisted invention by diving into an already potentially saturating field.

Artificial Intelligence Engineering Market Geographical Outlook:

  • The North American region is expected to hold a substantial artificial intelligence engineering market share.

The gradual shift of leading companies and brands in North America towards digitalization is promoting the automation of business operations and other related activities. Consequentially, this is generating a high demand for products engineered using artificial intelligence. The presence of international technology conglomerates such as Google and Amazon and the emergence of new AI software startups in the last few years, such as Cruise Automation, Palantir Technologies, and Tempus Labs in the US, are further creating market opportunities for AI engineering in North America.

In addition, Veritone analyzed the US BLS job report to understand the AI job trend in the country. Analysis of Aspen Tech Labs' Job Market Pulse then revealed a 32 percent increase in artificial intelligence jobs national listing compared to BLS aggregate, which is +14,117 job vacancies in April 2024 based upon a real-time database with more than five million U.S. jobs from 112 thousand employers. Hence, it can be anticipated that the North American AI engineering market will expand prominently over the forecast period.

Reasons for buying this report:-

  • Insightful Analysis: Gain detailed market insights covering major as well as emerging geographical regions, focusing on customer segments, government policies and socio-economic factors, consumer preferences, industry verticals, other sub- segments.
  • Competitive Landscape: Understand the strategic maneuvers employed by key players globally to understand possible market penetration with the correct strategy.
  • Market Drivers & Future Trends: Explore the dynamic factors and pivotal market trends and how they will shape up future market developments.
  • Actionable Recommendations: Utilize the insights to exercise strategic decision to uncover new business streams and revenues in a dynamic environment.
  • Caters to a Wide Audience: Beneficial and cost-effective for startups, research institutions, consultants, SMEs, and large enterprises.

What do businesses use our reports for?

Industry and Market Insights, Opportunity Assessment, Product Demand Forecasting, Market Entry Strategy, Geographical Expansion, Capital Investment Decisions, Regulatory Framework & Implications, New Product Development, Competitive Intelligence

Report Coverage:

  • Historical data & forecasts from 2022 to 2029
  • Growth Opportunities, Challenges, Supply Chain Outlook, Regulatory Framework, Customer Behaviour, and Trend Analysis
  • Competitive Positioning, Strategies, and Market Share Analysis
  • Revenue Growth and Forecast Assessment of segments and regions including countries
  • Company Profiling (Strategies, Products, Financial Information, and Key Developments among others)

Market Segmentation:

The Artificial Intelligence Engineering Market is segmented and analyzed as below:

By Technology

  • Deep Learning
  • Machine Learning
  • Natural Language Processing
  • Computer Vision

By Deployment

  • Cloud
  • On-premise

By Solution

  • Software
  • Services
  • Hardware

By End-User

  • Automotives
  • Communications
  • Manufacturing
  • Healthcare
  • Others

By Geography

  • North America
  • USA
  • Canada
  • Mexico
  • South America
  • Brazil
  • Argentina
  • Others
  • Europe
  • United Kingdom
  • Germany
  • France
  • Italy
  • Spain
  • Others
  • Middle East and Africa
  • Saudi Arabia
  • UAE
  • Others
  • Asia Pacific
  • China
  • Japan
  • India
  • South Korea
  • Australia
  • Singapore
  • Indonesia
  • Others

TABLE OF CONTENTS

1. INTRODUCTION

  • 1.1. Market Overview
  • 1.2. Market Definition
  • 1.3. Scope of the Study
  • 1.4. Market Segmentation
  • 1.5. Currency
  • 1.6. Assumptions
  • 1.7. Base and Forecast Years Timeline
  • 1.8. Key benefits for the stakeholders

2. RESEARCH METHODOLOGY

  • 2.1. Research Design
  • 2.2. Research Process

3. EXECUTIVE SUMMARY

  • 3.1. Key Findings

4. MARKET DYNAMICS

  • 4.1. Market Drivers
  • 4.2. Market Restraints
  • 4.3. Porter's Five Forces Analysis
    • 4.3.1. Bargaining Power of Suppliers
    • 4.3.2. Bargaining Power of Buyers
    • 4.3.3. Threat of New Entrants
    • 4.3.4. Threat of Substitutes
    • 4.3.5. Competitive Rivalry in the Industry
  • 4.4. Industry Value Chain Analysis
  • 4.5. Analyst View

5. ARTIFICIAL INTELLIGENCE ENGINEERING MARKET BY TECHNOLOGY

  • 5.1. Introduction
  • 5.2. Deep Learning
  • 5.3. Machine Learning
  • 5.4. Natural Language Processing
  • 5.5. Computer Vision

6. ARTIFICIAL INTELLIGENCE ENGINEERING MARKET BY DEPLOYMENT

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

7. ARTIFICIAL INTELLIGENCE ENGINEERING MARKET BY SOLUTION

  • 7.1. Introduction
  • 7.2. Software
  • 7.3. Services
  • 7.4. Hardware

8. ARTIFICIAL INTELLIGENCE ENGINEERING MARKET BY END-USER

  • 8.1. Introduction
  • 8.2. Automotives
  • 8.3. Communications
  • 8.4. Manufacturing
  • 8.5. Healthcare
  • 8.6. Others

9. ARTIFICIAL INTELLIGENCE ENGINEERING MARKET BY GEOGRAPHY

  • 9.1. Introduction
  • 9.2. North America
    • 9.2.1. By Technology
    • 9.2.2. By Deployment
    • 9.2.3. By Solution
    • 9.2.4. By End-User
    • 9.2.5. By Country
      • 9.2.5.1. USA
      • 9.2.5.2. Canada
      • 9.2.5.3. Mexico
  • 9.3. South America
    • 9.3.1. By Technology
    • 9.3.2. By Deployment
    • 9.3.3. By Solution
    • 9.3.4. By End-User
    • 9.3.5. By Country
      • 9.3.5.1. Brazil
      • 9.3.5.2. Argentina
      • 9.3.5.3. Others
  • 9.4. Europe
    • 9.4.1. By Technology
    • 9.4.2. By Deployment
    • 9.4.3. By Solution
    • 9.4.4. By End-User
    • 9.4.5. By Country
      • 9.4.5.1. United Kingdom
      • 9.4.5.2. Germany
      • 9.4.5.3. France
      • 9.4.5.4. Italy
      • 9.4.5.5. Spain
      • 9.4.5.6. Others
  • 9.5. Middle East and Africa
    • 9.5.1. By Technology
    • 9.5.2. By Deployment
    • 9.5.3. By Solution
    • 9.5.4. By End-User
    • 9.5.5. By Country
      • 9.5.5.1. Saudi Arabia
      • 9.5.5.2. UAE
      • 9.5.5.3. Others
  • 9.6. Asia Pacific
    • 9.6.1. By Technology
    • 9.6.2. By Deployment
    • 9.6.3. By Solution
    • 9.6.4. By End-User
    • 9.6.5. By Country
      • 9.6.5.1. China
      • 9.6.5.2. Japan
      • 9.6.5.3. India
      • 9.6.5.4. South Korea
      • 9.6.5.5. Australia
      • 9.6.5.6. Singapore
      • 9.6.5.7. Indonesia
      • 9.6.5.8. Others

10. COMPETITIVE ENVIRONMENT AND ANALYSIS

  • 10.1. Major Players and Strategy Analysis
  • 10.2. Market Share Analysis
  • 10.3. Mergers, Acquisitions, Agreements, and Collaborations
  • 10.4. Competitive Dashboard

11. COMPANY PROFILES

  • 11.1. Intel Corporation
  • 11.2. Microsoft Corporation
  • 11.3. Oracle Corporation
  • 11.4. IBM Corporation
  • 11.5. NVIDIA Corporation
  • 11.6. People.ai Inc
  • 11.7. Cisco Systems
  • 11.8. Verint Systems
  • 11.9. Salesforce
  • 11.10. Siemens AG