Ai Automation Testing Market
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
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
o US
o Canada
o Mexico
• Europe
o Germany
o UK
o Italy
o France
o Spain
o Rest of Europe
• Asia Pacific
o Japan
o China
o India
o Australia
o New Zealand
o South Korea
o Rest of Asia Pacific
• South America
o Argentina
o Brazil
o Chile
o Rest of South America
• Middle East & Africa
o Saudi Arabia
o UAE
o Qatar
o South Africa
o 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
o Comprehensive profiling of additional market players (up to 3)
o SWOT Analysis of key players (up to 3)
• Regional Segmentation
o Market estimations, Forecasts and CAGR of any prominent country as per the client's interest (Note: Depends on feasibility check)
• Competitive Benchmarking
o 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
1 Global AI Automation Testing Market Outlook, By Region (2021-2030) ($MN)
2 Global AI Automation Testing Market Outlook, By Component (2021-2030) ($MN)
3 Global AI Automation Testing Market Outlook, By Testing Type (2021-2030) ($MN)
4 Global AI Automation Testing Market Outlook, By Dynamic Testing (2021-2030) ($MN)
5 Global AI Automation Testing Market Outlook, By Functional Testing (2021-2030) ($MN)
6 Global AI Automation Testing Market Outlook, By API Testing (2021-2030) ($MN)
7 Global AI Automation Testing Market Outlook, By Performance Testing (2021-2030) ($MN)
8 Global AI Automation Testing Market Outlook, By Load Testing (2021-2030) ($MN)
9 Global AI Automation Testing Market Outlook, By Regression Testing (2021-2030) ($MN)
10 Global AI Automation Testing Market Outlook, By Security Testing (2021-2030) ($MN)
11 Global AI Automation Testing Market Outlook, By Static Testing (2021-2030) ($MN)
12 Global AI Automation Testing Market Outlook, By Service (2021-2030) ($MN)
13 Global AI Automation Testing Market Outlook, By Professional Services (2021-2030) ($MN)
14 Global AI Automation Testing Market Outlook, By Managed Services (2021-2030) ($MN)
15 Global AI Automation Testing Market Outlook, By Other Components (2021-2030) ($MN)
16 Global AI Automation Testing Market Outlook, By Deployment (2021-2030) ($MN)
17 Global AI Automation Testing Market Outlook, By Cloud (2021-2030) ($MN)
18 Global AI Automation Testing Market Outlook, By On-Premise (2021-2030) ($MN)
19 Global AI Automation Testing Market Outlook, By Organization Size (2021-2030) ($MN)
20 Global AI Automation Testing Market Outlook, By Large Enterprises (2021-2030) ($MN)
21 Global AI Automation Testing Market Outlook, By Small And Medium-Sized Enterprises (2021-2030) ($MN)
22 Global AI Automation Testing Market Outlook, By Technology (2021-2030) ($MN)
23 Global AI Automation Testing Market Outlook, By NLP (Natural Language Processing) (2021-2030) ($MN)
24 Global AI Automation Testing Market Outlook, By Machine Learning (2021-2030) ($MN)
25 Global AI Automation Testing Market Outlook, By MBTA (Model-Based Test Automation) (2021-2030) ($MN)
26 Global AI Automation Testing Market Outlook, By Computer Vision (2021-2030) ($MN)
27 Global AI Automation Testing Market Outlook, By Other Technologies (2021-2030) ($MN)
28 Global AI Automation Testing Market Outlook, By Application (2021-2030) ($MN)
29 Global AI Automation Testing Market Outlook, By Web-Based (2021-2030) ($MN)
30 Global AI Automation Testing Market Outlook, By Mobile-Based (2021-2030) ($MN)
31 Global AI Automation Testing Market Outlook, By End User (2021-2030) ($MN)
32 Global AI Automation Testing Market Outlook, By IT & Telecommunication (2021-2030) ($MN)
33 Global AI Automation Testing Market Outlook, By Healthcare (2021-2030) ($MN)
34 Global AI Automation Testing Market Outlook, By BFSI (2021-2030) ($MN)
35 Global AI Automation Testing Market Outlook, By Government (2021-2030) ($MN)
36 Global AI Automation Testing Market Outlook, By Defense And Aerospace (2021-2030) ($MN)
37 Global AI Automation Testing Market Outlook, By Energy & Utilities (2021-2030) ($MN)
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.
List of Figures
RESEARCH METHODOLOGY
We at ‘Stratistics’ opt for an extensive research approach which involves data mining, data validation, and data analysis. The various research sources include in-house repository, secondary research, competitor’s sources, social media research, client internal data, and primary research.
Our team of analysts prefers the most reliable and authenticated data sources in order to perform the comprehensive literature search. With access to most of the authenticated data bases our team highly considers the best mix of information through various sources to obtain extensive and accurate analysis.
Each report takes an average time of a month and a team of 4 industry analysts. The time may vary depending on the scope and data availability of the desired market report. The various parameters used in the market assessment are standardized in order to enhance the data accuracy.
Data Mining
The data is collected from several authenticated, reliable, paid and unpaid sources and is filtered depending on the scope & objective of the research. Our reports repository acts as an added advantage in this procedure. Data gathering from the raw material suppliers, distributors and the manufacturers is performed on a regular basis, this helps in the comprehensive understanding of the products value chain. Apart from the above mentioned sources the data is also collected from the industry consultants to ensure the objective of the study is in the right direction.
Market trends such as technological advancements, regulatory affairs, market dynamics (Drivers, Restraints, Opportunities and Challenges) are obtained from scientific journals, market related national & international associations and organizations.
Data Analysis
From the data that is collected depending on the scope & objective of the research the data is subjected for the analysis. The critical steps that we follow for the data analysis include:
- Product Lifecycle Analysis
- Competitor analysis
- Risk analysis
- Porters Analysis
- PESTEL Analysis
- SWOT Analysis
The data engineering is performed by the core industry experts considering both the Marketing Mix Modeling and the Demand Forecasting. The marketing mix modeling makes use of multiple-regression techniques to predict the optimal mix of marketing variables. Regression factor is based on a number of variables and how they relate to an outcome such as sales or profits.
Data Validation
The data validation is performed by the exhaustive primary research from the expert interviews. This includes telephonic interviews, focus groups, face to face interviews, and questionnaires to validate our research from all aspects. The industry experts we approach come from the leading firms, involved in the supply chain ranging from the suppliers, distributors to the manufacturers and consumers so as to ensure an unbiased analysis.
We are in touch with more than 15,000 industry experts with the right mix of consultants, CEO's, presidents, vice presidents, managers, experts from both supply side and demand side, executives and so on.
The data validation involves the primary research from the industry experts belonging to:
- Leading Companies
- Suppliers & Distributors
- Manufacturers
- Consumers
- Industry/Strategic Consultants
Apart from the data validation the primary research also helps in performing the fill gap research, i.e. providing solutions for the unmet needs of the research which helps in enhancing the reports quality.
For more details about research methodology, kindly write to us at info@strategymrc.com
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