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1438212

到 2030 年 AI 自動化測試市場預測：按組件、部署、組織規模、技術、應用程式、最終用戶和地區進行的全球分析

AI Automation Testing Market Forecasts to 2030 - Global Analysis By Component (Testing Type, Service and Electric), Deployment, Organization Size, Technology, Application End User and By Geography
出版日期: | 出版商: Stratistics Market Research Consulting | 英文 200+ Pages | 商品交期: 2-3個工作天內

價格

根據Stratistics MRC預測，2023年全球人工智慧自動化測試市場規模將達292億美元，預計2030年將達到953億美元，預測期內年複合成長率為18.4%。人工智慧自動化測試涉及使用人工智慧和機器學習來增強軟體測試過程。實現自動測試用例產生、執行和分析，以提高效率和準確性。人工智慧演算法透過識別模式、預測缺陷和最佳化測試來減少人工干涉。這種方法加快了測試生命週期，確保全面覆蓋，並提高了軟體發布的品質。該技術簡化了測試工作，識別漏洞，有助於提高軟體的整體可靠性，並滿足現代軟體開發實踐的需求。

加速軟體開發

快速、持續的發布需要高效、及時的測試。自動化測試中的人工智慧可以更快地識別缺陷，提高測試覆蓋率，並及早發現錯誤，從而加快測試生命週期。這種協同效應可確保應用程式得到徹底檢驗並為加快開發速度做好準備。隨著公司優先考慮軟體交付和採用的速度和質量，該市場在保持敏捷性、縮短上市時間和提高整體軟體可靠性方面發揮關鍵作用。

實施成本高

組織，尤其是規模較小的組織，可能會因獲取人工智慧工具、培訓人員和建立必要基礎設施所需的高昂前期成本而望而卻步。這種財務障礙限制了先進測試技術的使用，並阻礙了更廣泛的採用。意識到財務負擔可能會導致公司選擇傳統的測試方法，從而減緩市場擴張。

招募

隨著跨裝置、平台和配置的軟體生態系統變得越來越複雜，人工智慧主導的測試可確保彈性和擴充性。這種適應性解決了不同測試場景帶來的挑戰，從而提高了效率和全面的測試覆蓋範圍。尋求敏捷和響應式測試解決方案的公司重視回應動態環境的能力。

缺乏熟練的專業人員

測試和人工智慧方面專家的缺乏阻礙了先進測試技術的成功實施和利用。企業難以充分發揮人工智慧主導測試的潛力，導致實施緩慢且缺乏最佳化。這種稀缺性阻礙了人工智慧自動化測試解決方案的發展，並限制了它們對提高測試效率和整體軟體品質的影響。

COVID-19 的影響

雖然向數位轉型的轉變已經加速，並且對自動化測試解決方案的需求也在增加，但預算限制和資源限制卻減緩了採用速度。遠距工作情況也凸顯了強大的軟體測試的重要性以及對人工智慧主導的測試解決方案的興趣增加。疫情造成高效測試解決方案需求增加和實施挑戰的雙重影響，對AI自動化測試市場產生微妙影響。

機器學習領域預計將在預測期內成為最大的領域

隨著機器學習演算法實現智慧測試腳本生成、動態測試用例優先順序和自適應測試維護，機器學習領域預計將出現利潤豐厚的成長。其結果是更有效的缺陷識別和更大的測試覆蓋率。此外，機器學習有助於預測潛在問題、減少誤報並自動執行重複測試任務，從而促進市場成長。

預計基於行動的細分市場在預測期內將出現最高的年複合成長率

基於行動的細分市場預計在預測期內將以最高年複合成長率成長，以提高測試效率並確保跨不同行動平台的無縫功能。隨著行動應用開發的快速成長，需要嚴格的測試，而基於行動的人工智慧解決方案提供了更快、更準確的測試過程。隨著行動技術的不斷發展，整合人工智慧自動化測試對於企業確保行動應用程式健壯可靠並滿足最終用戶的動態期望至關重要。

比最大的地區

在預測期內，由於自動化測試的顯著擴張，預計北美將佔據最大的市場佔有率。隨著行動應用程式變得越來越複雜，人工智慧回歸測試的使用越來越多，影響了北美的人工智慧測試。此外，由於技術供應商的存在，美國預計在整個預測期內將取得顯著發展。該市場的擴張是由都市化加快、生活方式不斷變化、可支配收入增加和技術進步等因素所推動的。

年複合成長率最高的地區：

由於研發費用增加、對自動化測試解決方案的需求不斷成長、新產品推出等，預計亞太地區在預測期內將呈現最高的年複合成長率。為了支持市場擴張，中國、日本和印度等亞太國家正在開發和推出新平台和產品。此外，由於對自動化和有效的通訊基礎設施測試和維護的需求可能會激增，日本人工智慧驅動的測試技術的使用可能會增加。

提供免費客製化：

訂閱此報告的客戶可以存取以下免費自訂選項之一：

  • 公司簡介
    • 其他市場參與者的綜合分析（最多 3 家公司）
    • 主要企業SWOT分析（最多3家企業）
  • 區域分割
    • 根據客戶興趣對主要國家的市場估計、預測和年複合成長率（註：基於可行性檢查）
  • 競爭基準化分析
    • 根據產品系列、地理分佈和策略聯盟對主要企業基準化分析

目錄

第1章執行摘要

第2章 前言

  • 概述
  • 相關利益者
  • 調查範圍
  • 調查方法
    • 資料探勘
    • 資料分析
    • 資料檢驗
    • 研究途徑
  • 調查來源
    • 主要調查來源
    • 二次調查來源
    • 先決條件

第3章市場趨勢分析

  • 促進因素
  • 抑制因素
  • 機會
  • 威脅
  • 技術分析
  • 應用分析
  • 最終用戶分析
  • 新興市場
  • 新型冠狀病毒感染疾病（COVID-19）的影響

第4章波特五力分析

  • 供應商的議價能力
  • 買方議價能力
  • 替代品的威脅
  • 新進入者的威脅
  • 競爭公司之間的敵對關係

第5章全球人工智慧自動化測試市場：按組成部分

  • 測試類型
    • 動態測試
      • 功能測試
      • API測試
      • 性能測試
      • 壓力測試
      • 回歸測試
      • 安全測試
    • 靜態測試
  • 服務
    • 專業服務
    • 管理服務
  • 其他組件

第6章 全球人工智慧自動化測試市場：按部署分類

  • 雲
  • 本地

第7章 全球人工智慧自動化測試市場：依組織規模分類

  • 主要企業
  • 中小企業

第8章全球人工智慧自動化測試市場：依技術分類

  • NLP（自然語言處理）
  • 機器學習
  • MBTA（基於模型的測試自動化）
  • 電腦視覺
  • 其他技術

第9章 全球人工智慧自動化測試市場：按應用分類

  • 基於網路的
  • 移動基地

第10章 全球人工智慧自動化測試市場：依最終使用者分類

  • 資訊科技和通訊
  • 衛生保健
  • BFSI
  • 政府
  • 國防和航太
  • 能源和公共
  • 其他最終用戶

第11章 全球人工智慧自動化測試市場：按地區

  • 北美洲
    • 美國
    • 加拿大
    • 墨西哥
  • 歐洲
    • 德國
    • 英國
    • 義大利
    • 法國
    • 西班牙
    • 其他歐洲國家
  • 亞太地區
    • 日本
    • 中國
    • 印度
    • 澳洲
    • 紐西蘭
    • 韓國
    • 其他亞太地區
  • 南美洲
    • 阿根廷
    • 巴西
    • 智利
    • 南美洲其他地區
  • 中東和非洲
    • 沙烏地阿拉伯
    • 阿拉伯聯合大公國
    • 卡達
    • 南非
    • 其他中東和非洲

第12章 主要進展

  • 合約、夥伴關係、協作和合資企業
  • 收購和合併
  • 新產品發布
  • 業務擴展
  • 其他關鍵策略

第13章 公司簡介

  • Apexon
  • Applitools
  • Capgemini SE
  • D2L Corp.
  • Functionize Inc.
  • IBM Corporation
  • Keysight technologies
  • Mabl Inc.
  • Micro Focus International Plc
  • Open Text
  • Parasoft
  • Perforce Software, In
  • ReTest GmbH
  • Sauce Labs Inc.
  • Testim
  • testRigor
  • Tricentis
  • UBS Hainer GmbH
Product Code: SMRC25181

According to Stratistics MRC, the Global AI Automation Testing Market is accounted for $29.2 billion in 2023 and is expected to reach $95.3 billion by 2030 growing at a CAGR of 18.4% during the forecast period. AI Automation Testing involves the use of artificial intelligence and machine learning to enhance software testing processes. It enables automated test case generation, execution, and analysis, improving efficiency and accuracy. AI algorithms identify patterns, predict defects, and optimize testing, reducing manual intervention. This approach accelerates the testing lifecycle, ensures comprehensive coverage, and enhances the quality of software releases. The technology streamlines testing efforts, identifies vulnerabilities, and contributes to overall software reliability, meeting the demands of modern software development practices.

Market Dynamics:

Driver:

Accelerated software development

The need for rapid and continuous releases requires efficient and timely testing. AI in automation testing expedites the testing lifecycle, offering quick identification of defects, increased test coverage, and early bug detection. This synergy ensures that applications are thoroughly validated, aligning with the accelerated development pace. As organizations prioritize speed and quality in software delivery, the market experiences heightened adoption, playing a pivotal role in maintaining agility, reducing time-to-market, and enhancing overall software reliability.

Restraint:

High implementation cost

Organizations, particularly smaller ones, may be deterred by the substantial upfront expenses involved in acquiring AI tools, training personnel, and establishing the necessary infrastructure. This financial barrier limits the accessibility of advanced testing technologies, hindering broader adoption. The perceived financial burden could lead businesses to opt for traditional testing methods, slowing down the market expansion.

Opportunity:

Adoption

As software ecosystems become increasingly complex with varied devices, platforms, and configurations, AI-driven testing ensures flexibility and scalability. This adaptability addresses the challenges posed by diverse testing scenarios, leading to improved efficiency and comprehensive test coverage. Organizations seeking agile and responsive testing solutions value the capability to handle dynamic environments.

Threat:

Shortage of skilled professionals

The lack of experts proficient in both testing and AI impedes the successful implementation and utilization of advanced testing technologies. Companies face difficulties in harnessing the full potential of AI-driven testing, leading to delayed or suboptimal adoption. This scarcity hampers the growth of AI Automation Testing solutions, limiting their impact on improving testing efficiency and overall software quality.

Covid-19 Impact

While the demand for automated testing solutions increased due to the accelerated shift towards digital transformation, budget constraints and resource limitations slowed down adoption. Remote working conditions also highlighted the importance of robust software testing, driving interest in AI-driven testing solutions. The pandemic created a dual effect of increased demand for efficient testing solutions and challenges in implementation, resulting in a nuanced impact on the AI Automation Testing market.

The machine learning segment is expected to be the largest during the forecast period

The machine learning segment is estimated to have a lucrative growth, because the machine learning algorithms enable intelligent test script generation, dynamic test case prioritization, and adaptive test maintenance. This results in more effective identification of defects and improved testing coverage. Additionally, machine learning aids in predicting potential issues, reducing false positives, and automating repetitive testing tasks boosting the market growth.

The mobile-based segment is expected to have the highest CAGR during the forecast period

The mobile-based segment is anticipated to witness the highest CAGR growth during the forecast period, as it enhances testing efficiency, ensuring seamless functionality across diverse mobile platforms. The surge in mobile app development demands rigorous testing, and mobile-based AI solutions provide quicker, more accurate testing processes. As mobile technologies continue to evolve, the integration of AI automation testing becomes imperative for businesses to ensure robust and reliable mobile applications, meeting the dynamic expectations of end-users

Region with largest share:

North America is projected to hold the largest market share during the forecast period driven by the notable expansion of automated testing. As mobile apps become more functional, AI regression testing is being utilized more and more, which is impacting AI-enabled testing in North America. Furthermore, because of the existence of technology suppliers, the United States is anticipated to develop greatly throughout the projection period. The expansion of this market is driven by factors such as growing urbanization, evolving lifestyles, increased disposable income, and enhanced technology.

Region with highest CAGR:

Asia Pacific is projected to have the highest CAGR over the forecast period, owing to rising R&D spending, rising demand for automated testing solutions, and the introduction of new products. To support market expansion, Asia Pacific nations like China, Japan, India, and others are developing and introducing new platforms and goods. Additionally a possible upsurge in demand for automated and effective telecom infrastructure testing and maintenance may lead to a rise in the use of AI-enabled testing technologies in Japan.

Key players in the market

Some of the key players in the AI Automation Testing Market include Apexon, Applitools, Capgemini SE, D2L Corp., Functionize Inc., IBM Corporation, Keysight technologies, Mabl Inc., Micro Focus International Plc, Open Text, Parasoft, Perforce Software In, ReTest GmbH, Sauce Labs Inc., Testim, testRigor, Tricentis and UBS Hainer GmbH

Key Developments:

In December 2023, Apexon, a digital-first technology services company, today announced that Microsoft has named it a Solutions Partner for Data and AI. This prestigious accolade follows the company's recent achievements in securing the Microsoft Digital and App Innovation, and Infrastructure Solutions Partner designations

In August 2023, Apexon, has expanded its presence in India by setting up a new facility in Ahmedabad. The new delivery center will leverage the rich engineering talent pool in Ahmedabad and India and further strengthen Apexon's ability to deliver digital and business transformation for its global client base.

In July 2023, Applitools Partners with Sogeti on '2021 State of Artificial Intelligence Applied to Quality Engineering Report. Sogeti will introduce each follow-on section of the full report every two weeks from September to the end of January

Components Covered:

  • Testing Type
  • Service
  • Other Components

Deployments Covered:

  • Cloud
  • On-Premise

Organization Sizes Covered:

  • Large Enterprises
  • Small And Medium-Sized Enterprises

Technologies Covered:

  • NLP (Natural Language Processing)
  • Machine Learning
  • MBTA (Model-Based Test Automation)
  • Computer Vision
  • Other Technologies

Applications Covered:

  • Web-Based
  • Mobile-Based

End Users Covered:

  • IT & Telecommunication
  • Healthcare
  • BFSI
  • Government
  • Defense And Aerospace
  • Energy & Utilities
  • Other End Users

Regions Covered:

  • North America
    • US
    • Canada
    • Mexico
  • Europe
    • Germany
    • UK
    • Italy
    • France
    • Spain
    • Rest of Europe
  • Asia Pacific
    • Japan
    • China
    • India
    • Australia
    • New Zealand
    • South Korea
    • Rest of Asia Pacific
  • South America
    • Argentina
    • Brazil
    • Chile
    • Rest of South America
  • Middle East & Africa
    • Saudi Arabia
    • UAE
    • Qatar
    • South Africa
    • Rest of Middle East & Africa

What our report offers:

  • Market share assessments for the regional and country-level segments
  • Strategic recommendations for the new entrants
  • Covers Market data for the years 2021, 2022, 2023, 2026, and 2030
  • Market Trends (Drivers, Constraints, Opportunities, Threats, Challenges, Investment Opportunities, and recommendations)
  • Strategic recommendations in key business segments based on the market estimations
  • Competitive landscaping mapping the key common trends
  • Company profiling with detailed strategies, financials, and recent developments
  • Supply chain trends mapping the latest technological advancements

Free Customization Offerings:

All the customers of this report will be entitled to receive one of the following free customization options:

  • Company Profiling
    • Comprehensive profiling of additional market players (up to 3)
    • SWOT Analysis of key players (up to 3)
  • Regional Segmentation
    • Market estimations, Forecasts and CAGR of any prominent country as per the client's interest (Note: Depends on feasibility check)
  • Competitive Benchmarking
    • Benchmarking of key players based on product portfolio, geographical presence, and strategic alliances

Table of Contents

1 Executive Summary

2 Preface

  • 2.1 Abstract
  • 2.2 Stake Holders
  • 2.3 Research Scope
  • 2.4 Research Methodology
    • 2.4.1 Data Mining
    • 2.4.2 Data Analysis
    • 2.4.3 Data Validation
    • 2.4.4 Research Approach
  • 2.5 Research Sources
    • 2.5.1 Primary Research Sources
    • 2.5.2 Secondary Research Sources
    • 2.5.3 Assumptions

3 Market Trend Analysis

  • 3.1 Introduction
  • 3.2 Drivers
  • 3.3 Restraints
  • 3.4 Opportunities
  • 3.5 Threats
  • 3.6 Technology Analysis
  • 3.7 Application Analysis
  • 3.8 End User Analysis
  • 3.9 Emerging Markets
  • 3.10 Impact of Covid-19

4 Porters Five Force Analysis

  • 4.1 Bargaining power of suppliers
  • 4.2 Bargaining power of buyers
  • 4.3 Threat of substitutes
  • 4.4 Threat of new entrants
  • 4.5 Competitive rivalry

5 Global AI Automation Testing Market, By Component

  • 5.1 Introduction
  • 5.2 Testing Type
    • 5.2.1 Dynamic Testing
      • 5.2.1.1 Functional Testing
      • 5.2.1.2 API Testing
      • 5.2.1.3 Performance Testing
      • 5.2.1.4 Load Testing
      • 5.2.1.5 Regression Testing
      • 5.2.1.6 Security Testing
    • 5.2.2 Static Testing
  • 5.3 Service
    • 5.3.1 Professional Services
    • 5.3.2 Managed Services
  • 5.4 Other Components

6 Global AI Automation Testing Market, By Deployment

  • 6.1 Introduction
  • 6.2 Cloud
  • 6.3 On-Premise

7 Global AI Automation Testing Market, By Organization Size

  • 7.1 Introduction
  • 7.2 Large Enterprises
  • 7.3 Small And Medium-Sized Enterprises

8 Global AI Automation Testing Market, By Technology

  • 8.1 Introduction
  • 8.2 NLP (Natural Language Processing)
  • 8.3 Machine Learning
  • 8.4 MBTA (Model-Based Test Automation)
  • 8.5 Computer Vision
  • 8.6 Other Technologies

9 Global AI Automation Testing Market, By Application

  • 9.1 Introduction
  • 9.2 Web-Based
  • 9.3 Mobile-Based

10 Global AI Automation Testing Market, By End User

  • 10.1 Introduction
  • 10.2 IT & Telecommunication
  • 10.3 Healthcare
  • 10.4 BFSI
  • 10.5 Government
  • 10.6 Defense And Aerospace
  • 10.7 Energy & Utilities
  • 10.8 Other End Users

11 Global AI Automation Testing Market, By Geography

  • 11.1 Introduction
  • 11.2 North America
    • 11.2.1 US
    • 11.2.2 Canada
    • 11.2.3 Mexico
  • 11.3 Europe
    • 11.3.1 Germany
    • 11.3.2 UK
    • 11.3.3 Italy
    • 11.3.4 France
    • 11.3.5 Spain
    • 11.3.6 Rest of Europe
  • 11.4 Asia Pacific
    • 11.4.1 Japan
    • 11.4.2 China
    • 11.4.3 India
    • 11.4.4 Australia
    • 11.4.5 New Zealand
    • 11.4.6 South Korea
    • 11.4.7 Rest of Asia Pacific
  • 11.5 South America
    • 11.5.1 Argentina
    • 11.5.2 Brazil
    • 11.5.3 Chile
    • 11.5.4 Rest of South America
  • 11.6 Middle East & Africa
    • 11.6.1 Saudi Arabia
    • 11.6.2 UAE
    • 11.6.3 Qatar
    • 11.6.4 South Africa
    • 11.6.5 Rest of Middle East & Africa

12 Key Developments

  • 12.1 Agreements, Partnerships, Collaborations and Joint Ventures
  • 12.2 Acquisitions & Mergers
  • 12.3 New Product Launch
  • 12.4 Expansions
  • 12.5 Other Key Strategies

13 Company Profiling

  • 13.1 Apexon
  • 13.2 Applitools
  • 13.3 Capgemini SE
  • 13.4 D2L Corp.
  • 13.5 Functionize Inc.
  • 13.6 IBM Corporation
  • 13.7 Keysight technologies
  • 13.8 Mabl Inc.
  • 13.9 Micro Focus International Plc
  • 13.10 Open Text
  • 13.11 Parasoft
  • 13.12 Perforce Software, In
  • 13.13 ReTest GmbH
  • 13.14 Sauce Labs Inc.
  • 13.15 Testim
  • 13.16 testRigor
  • 13.17 Tricentis
  • 13.18 UBS Hainer GmbH

List of Tables

  • Table 1 Global AI Automation Testing Market Outlook, By Region (2021-2030) ($MN)
  • Table 2 Global AI Automation Testing Market Outlook, By Component (2021-2030) ($MN)
  • Table 3 Global AI Automation Testing Market Outlook, By Testing Type (2021-2030) ($MN)
  • Table 4 Global AI Automation Testing Market Outlook, By Dynamic Testing (2021-2030) ($MN)
  • Table 5 Global AI Automation Testing Market Outlook, By Functional Testing (2021-2030) ($MN)
  • Table 6 Global AI Automation Testing Market Outlook, By API Testing (2021-2030) ($MN)
  • Table 7 Global AI Automation Testing Market Outlook, By Performance Testing (2021-2030) ($MN)
  • Table 8 Global AI Automation Testing Market Outlook, By Load Testing (2021-2030) ($MN)
  • Table 9 Global AI Automation Testing Market Outlook, By Regression Testing (2021-2030) ($MN)
  • Table 10 Global AI Automation Testing Market Outlook, By Security Testing (2021-2030) ($MN)
  • Table 11 Global AI Automation Testing Market Outlook, By Static Testing (2021-2030) ($MN)
  • Table 12 Global AI Automation Testing Market Outlook, By Service (2021-2030) ($MN)
  • Table 13 Global AI Automation Testing Market Outlook, By Professional Services (2021-2030) ($MN)
  • Table 14 Global AI Automation Testing Market Outlook, By Managed Services (2021-2030) ($MN)
  • Table 15 Global AI Automation Testing Market Outlook, By Other Components (2021-2030) ($MN)
  • Table 16 Global AI Automation Testing Market Outlook, By Deployment (2021-2030) ($MN)
  • Table 17 Global AI Automation Testing Market Outlook, By Cloud (2021-2030) ($MN)
  • Table 18 Global AI Automation Testing Market Outlook, By On-Premise (2021-2030) ($MN)
  • Table 19 Global AI Automation Testing Market Outlook, By Organization Size (2021-2030) ($MN)
  • Table 20 Global AI Automation Testing Market Outlook, By Large Enterprises (2021-2030) ($MN)
  • Table 21 Global AI Automation Testing Market Outlook, By Small And Medium-Sized Enterprises (2021-2030) ($MN)
  • Table 22 Global AI Automation Testing Market Outlook, By Technology (2021-2030) ($MN)
  • Table 23 Global AI Automation Testing Market Outlook, By NLP (Natural Language Processing) (2021-2030) ($MN)
  • Table 24 Global AI Automation Testing Market Outlook, By Machine Learning (2021-2030) ($MN)
  • Table 25 Global AI Automation Testing Market Outlook, By MBTA (Model-Based Test Automation) (2021-2030) ($MN)
  • Table 26 Global AI Automation Testing Market Outlook, By Computer Vision (2021-2030) ($MN)
  • Table 27 Global AI Automation Testing Market Outlook, By Other Technologies (2021-2030) ($MN)
  • Table 28 Global AI Automation Testing Market Outlook, By Application (2021-2030) ($MN)
  • Table 29 Global AI Automation Testing Market Outlook, By Web-Based (2021-2030) ($MN)
  • Table 30 Global AI Automation Testing Market Outlook, By Mobile-Based (2021-2030) ($MN)
  • Table 31 Global AI Automation Testing Market Outlook, By End User (2021-2030) ($MN)
  • Table 32 Global AI Automation Testing Market Outlook, By IT & Telecommunication (2021-2030) ($MN)
  • Table 33 Global AI Automation Testing Market Outlook, By Healthcare (2021-2030) ($MN)
  • Table 34 Global AI Automation Testing Market Outlook, By BFSI (2021-2030) ($MN)
  • Table 35 Global AI Automation Testing Market Outlook, By Government (2021-2030) ($MN)
  • Table 36 Global AI Automation Testing Market Outlook, By Defense And Aerospace (2021-2030) ($MN)
  • Table 37 Global AI Automation Testing Market Outlook, By Energy & Utilities (2021-2030) ($MN)
  • Table 38 Global AI Automation Testing Market Outlook, By Other End Users (2021-2030) ($MN)

Note: Tables for North America, Europe, APAC, South America, and Middle East & Africa Regions are also represented in the same manner as above.