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市場調查報告書
商品編碼
1574124

人工智慧工程市場：2024-2029 年預測

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個工作天內

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簡介目錄

人工智慧工程市場預計將從 2024 年的 109.04 億美元增至 2029 年的 480.74 億美元，預測期內複合年成長率為 34.54%。

人工智慧工程是一個跨學科領域，它客製化和整合電腦科學概念和資訊技術基礎設施，以開發新的人工智慧軟體解決方案和工具，可應用於現實世界中的各種行業。人工智慧工程師根據目標客戶和產業需求，利用深度學習概念、機器學習模型、自然語言處理能力、神經網路系統演算法、電腦視覺技術等開發各種人工智慧產品。

此外，由於人工智慧技術具有眾多優勢，汽車、醫療保健、零售、通訊和製造等各行業的公司正在將基於人工智慧的軟體、硬體和服務納入其業務營運。因此，在預測期內，人工智慧技術的廣泛接受以及大多數經濟領域對人工智慧驅動的技術解決方案的需求不斷增加，可能會推動人工智慧工程市場的進一步擴張。

人工智慧工程市場的促進因素：

  • 對業務自動化的需求不斷成長預計將推動市場成長。

最大限度地提高業務任務的業務並透過減少人為錯誤來提高準確性水平正在推動業務。根據IBM 2023年發布的《IBM全球人工智慧採用指數》，大約42%的企業級組織正在業務中使用人工智慧，59%的企業計劃儘早利用人工智慧並擴大投資。最積極使用人工智慧的行業是金融服務和通訊，金融服務領域近一半的 IT 專業人員表示在其公司中實施了人工智慧，而通訊業的 IT 專家也報告了類似比例 (37%)。

因此，對業務自動化的需求不斷成長以及各行業對人工智慧技術的採用正在推動人工智慧工程市場的發展。例如，2024 年 4 月，微軟和 Iprova 合作主辦了人工智慧輔助發明高峰會。本次高峰會旨在共用人工智慧輔助發明的現實經驗、挑戰和未解決的問題。本次研討會面向技術專家、相關人員以及人工智慧輔助發明的現有和未來的新用戶，以深入研究可能已經飽和狀態的領域。

人工智慧工程市場地域展望：

  • 北美地區預計將佔據人工智慧工程市場的重要佔有率。

主要企業和品牌逐漸轉向數位化，正在推動業務營運和其他相關活動的自動化。因此，對人工智慧產品的需求不斷增加。 Google、亞馬遜等國際科技巨頭的出現，以及近年來美國Cruise Automation、Palantir Technologies、Tempus Labs等新型人工智慧軟體新興企業的出現，進一步增加了北美人工智慧工程的市場機會正在生產。

此外，Veritone還分析了美國勞工統計局的就業報告，以了解該國的人工智慧招募趨勢。根據 Aspen Tech Labs 的就業市場脈搏的分析，與 BLS 的統計數據相比，國內人工智慧職缺增加了 32%，根據我們的即時資料庫，該數據匯總了來自 112,000 名雇主的超過 500 萬個美國職位空缺。因此，北美人工智慧工程市場預計在預測期內將大幅擴張。

為什麼要購買這份報告？

  • 洞察分析：深入洞察關鍵和新興地區的市場，重點關注客戶細分、政府政策、社會經濟因素、消費者偏好、產業和其他子區隔。
  • 競爭格局：了解世界各地主要企業採取的策略策略，並了解採用正確策略滲透市場的潛力。
  • 市場促進因素和未來趨勢：檢視動態因素和關鍵市場趨勢，並探討它們將如何影響未來的市場發展。
  • 可行的建議：利用洞察力做出策略決策，在動態環境中發現新的業務流和收益。
  • 迎合廣泛的受眾：對於新興企業、研究機構、顧問、中小型企業和大型企業來說有用且具有成本效益。

公司使用我們的報告的目的是什麼？

產業和市場考量、機會評估、產品需求預測、打入市場策略、地理擴張、資本投資決策、法律規範與影響、新產品開拓、競爭影響

調查範圍

  • 過去的資料/預測，2022-2029
  • 成長機會、挑戰、供應鏈前景、法規結構、顧客行為、趨勢分析
  • 競爭定位、策略和市場佔有率分析
  • 區域收益成長和預測分析，包括細分市場和國家
  • 公司概況（策略、產品、財務資訊、主要發展等）

目錄

第1章簡介

  • 市場概況
  • 市場定義
  • 調查範圍
  • 市場區隔
  • 貨幣
  • 先決條件
  • 基準年和預測年時間表
  • 相關人員的主要利益

第2章調查方法

  • 研究設計
  • 調查過程

第3章執行摘要

  • 主要發現

第4章市場動態

  • 市場促進因素
  • 市場限制因素
  • 波特五力分析
  • 產業價值鏈分析
  • 分析師觀點

第5章 人工智慧工程市場：依技術分類

  • 介紹
  • 深度學習
  • 機器學習
  • 自然語言處理
  • 電腦視覺

第6章 人工智慧工程市場：依發展分類

  • 介紹
  • 雲
  • 本地

第7章 人工智慧工程市場：按解決方案

  • 介紹
  • 軟體
  • 服務
  • 硬體

第8章人工智慧工程市場：依最終用戶分類

  • 介紹
  • 車
  • 溝通
  • 製造業
  • 衛生保健
  • 其他

第9章 人工智慧工程市場：按地區

  • 介紹
  • 北美洲
    • 依技術
    • 按發展
    • 按解決方案
    • 按最終用戶
    • 按國家/地區
  • 南美洲
    • 依技術
    • 按發展
    • 按解決方案
    • 按最終用戶
    • 按國家/地區
  • 歐洲
    • 依技術
    • 按發展
    • 按解決方案
    • 按最終用戶
    • 按國家/地區
  • 中東/非洲
    • 依技術
    • 按發展
    • 按解決方案
    • 按最終用戶
    • 按國家/地區
  • 亞太地區
    • 依技術
    • 按發展
    • 按解決方案
    • 按最終用戶
    • 按國家/地區

第10章競爭環境及分析

  • 主要企業及策略分析
  • 市場佔有率分析
  • 合併、收購、協議和合作
  • 競爭對手儀表板

第11章 公司簡介

  • Intel Corporation
  • Microsoft Corporation
  • Oracle Corporation
  • IBM Corporation
  • NVIDIA Corporation
  • People.ai Inc
  • Cisco Systems
  • Verint Systems
  • Salesforce
  • Siemens AG
簡介目錄
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