AI 기반 테스트 시장 규모, 점유율, 성장 및 세계 산업 분석 : 유형별, 용도별, 지역별 인사이트와 예측(2026-2034년)

Growth Factors of AI-enabled testing Market

The global AI-enabled testing market is witnessing significant growth due to increasing adoption of artificial intelligence, machine learning, and related technologies in software quality assurance. AI-enabled testing automates test case creation, execution, and defect identification, improving software performance and enhancing user experience. These solutions enable testers to save time, increase test coverage, and develop self-curative and reusable test cases, thereby improving efficiency and accuracy.

According to Fortune Business Insights, the market was valued at USD 1.01 billion in 2025, projected to reach USD 1.21 billion in 2026, and expand to USD 4.64 billion by 2034, with a CAGR of 18.30%. North America dominated the market in 2025 with a 34.60% share, driven by strong IT infrastructure, high adoption of emerging technologies, and presence of major software testing vendors.

COVID-19 Impact

The COVID-19 pandemic accelerated the adoption of AI-enabled testing solutions, as enterprises shifted operations online and faced heightened risks from software failures. AI-enabled testing provided faster bug detection, minimized QA costs, and improved time-to-market. During the pandemic, major collaborations, such as Appvance with PwC Australia in 2020, introduced AI-powered combined test automation systems, further fueling market growth. These solutions ensured continuity in operations, prevented data loss, and improved testing efficiency across industries.

Market Trends

One of the key trends driving the market is the implementation of AI-driven security testing. AI enables identification of vulnerabilities, threat prevention, and integration of security testing into every phase of the Software Development Life Cycle (SDLC). In November 2023, GitHub launched AI-driven application security testing, featuring autofix for code scanning, secret scanning for leaked passwords, and custom expression generators, strengthening security capabilities and accelerating market growth.

Growth Factors

The rising demand for no-code or codeless AI testing platforms is boosting market expansion. Low-code platforms allow stakeholders with limited coding knowledge to build AI-driven test cases, streamlining test automation and making it accessible to a wider audience. By 2025, nearly 70% of newly developed enterprise solutions are expected to use low-code or no-code technologies. For instance, SofySense (April 2023) combines generative AI with no-code mobile application testing, enhancing efficiency, QA assistance, and automation capabilities.

Restraining Factors

AI-enabled testing is highly data-dependent, and biased or insufficient datasets can produce inaccurate or unfair results. Limited data can reduce the model's ability to detect edge cases, creating potential gaps in software testing. Developers must prioritize diverse and representative datasets to minimize bias and enhance testing accuracy.

Market Segmentation Analysis

By Deployment:

• Cloud-based solutions dominate with 62.80% market share in 2026, providing cost efficiency, global accessibility, faster testing cycles, and real-time collaboration.
• On-premise solutions offer enhanced privacy and customizable testing environments, holding a substantial share.

By Application:

• Web-based applications held 70.24% market share in 2026, due to ease of use, scalability, and broad adoption across API testing, regression testing, and automated web testing.
• Mobile-based testing provides flexibility to test apps directly on smartphones and tablets, gaining gradual adoption.

By Technology:

• Machine learning leads with 37.48% share in 2026, optimizing test sets and automating scripts efficiently.
• Computer vision is growing rapidly, applied in IoT, automotive, marketing, and mobile testing. Collaborations like Anyverse with Tech Mahindra (2023) highlight growth in computer vision testing solutions.

By Industry:

• IT & telecom holds 36.24% market share in 2026, leveraging AI testing for network, server, and application performance optimization.
• Healthcare is expected to grow fastest, using AI for real-time analysis, predictive modeling, bias detection, and data pattern recognition in medical applications.

Regional Insights

• North America: Market size USD 0.35B in 2025, projected USD 0.21B in 2026, driven by U.S. investments in AI-enabled testing and presence of top vendors like Functionize, Tricentis, and Mabl.
• Asia Pacific: Highest growth potential; Japan USD 0.07B, China USD 0.09B, India USD 0.05B in 2026, supported by investments in AI, machine learning, and NLP technologies.
• Europe: Rapid adoption in Germany, Spain, Italy, France; UK USD 0.1B, Germany USD 0.07B in 2026, driven by government initiatives and innovation in AI testing.
• Middle East & Africa, South America: Moderate growth fueled by AI and robotics adoption, digital economy development, and enterprise demand.

Key Industry Players & Developments

Top companies include Functionize, Sauce Labs, Tricentis, Diffblue, Applitools, Mabl, UBS Hainer, Testim, Perforce Software, and Open Text (MicroFocus). Notable developments:

• Nov 2023: Mabl integrated with GitLab for AI-powered DevSecOps testing.
• Sep 2023: Perforce Software added generative AI to BlazeMeter Test Data Pro.
• Oct 2023: Katalon launched TrueTest with AI-based testing capabilities.
• May 2023: UiPath introduced AI-driven automation for SAP testing.

Conclusion

In conclusion, the AI-enabled testing market is projected to grow from USD 1.01 billion in 2025 to USD 4.64 billion by 2034, at a CAGR of 18.30%, driven by AI integration, no-code solutions, cloud adoption, and demand in IT & telecom and healthcare sectors. Despite challenges such as data dependency and bias, emerging technologies, strategic partnerships, and innovations by key players will continue to drive global market expansion and improve software testing efficiency across industries.

Segmentation By Deployment

• Cloud
• On-premise

By Application

• Web-based
• Mobile-based

By Technology

• Machine Learning
• NLP (Natural Language Processing)
• Computer Vision
• MBTA (Model-based Test Automation)
• Others (RPA)

By Industry

• IT & Telecom
• BFSI
• Healthcare
• Energy & Utilities
• Others (Government, Education, and Manufacturing)

By Region

• North America (By Deployment, Application, Technology, Industry, and Country)
  • U.S. (By Industry)
  • Canada (By Industry)
  • Mexico (By Industry)
• Europe (By Deployment, Application, Technology, Industry, and Country)
  • U.K. (By Industry)
  • Germany (By Industry)
  • France (By Industry)
  • Italy (By Industry)
  • Spain (By Industry)
  • Russia (By Industry)
  • Benelux (By Industry)
  • Nordics (By Industry)
  • Rest of Europe
• Asia Pacific (By Deployment, Application, Technology, Industry, and Country)
  • China (By Industry)
  • Japan (By Industry)
  • India (By Industry)
  • South Korea (By Industry)
  • ASEAN (By Industry)
  • Oceania (By Industry)
  • Rest of the Asia Pacific
• Middle East & Africa (By Deployment, Application, Technology, Industry, and Country)
  • Turkey (By Industry)
  • Israel (By Industry)
  • GCC (By Industry)
  • North Africa (By Industry)
  • South Africa (By Industry)
  • Rest of the Middle East & Africa
• South America (By Deployment, Application, Technology, Industry, and Country)
  • Brazil (By Industry)
  • Argentina (By Industry)
  • Rest of South America

Table of Content

1. Introduction

• 1.1. Definition, By Segment
• 1.2. Research Methodology/Approach
• 1.3. Data Sources

2. Executive Summary

3. Market Dynamics

• 3.1. Macro and Micro Economic Indicators
• 3.2. Drivers, Restraints, Opportunities and Trends
• 3.3. Impact of COVID-19

4. Competition Landscape

• 4.1. Business Strategies Adopted by Key Players
• 4.2. Consolidated SWOT Analysis of Key Players
• 4.3. Global AI-enabled Testing Key Players Market Share/Ranking, 2025

5. Global AI-enabled Testing Market Size Estimates and Forecasts, By Segments, 2021-2034

• 5.1. Key Findings
• 5.2. By Deployment (USD)
  • 5.2.1. Cloud
  • 5.2.2. On-premise
• 5.3. By Application (USD)
  • 5.3.1. Web-based
  • 5.3.2. Mobile-based
• 5.4. By Technology (USD)
  • 5.4.1. Machine Learning
  • 5.4.2. NLP (Natural Language Processing)
  • 5.4.3. Computer Vision
  • 5.4.4. MBTA (Model-based test automation)
  • 5.4.5. Others (RPA, etc.)
• 5.5. By Industry (USD)
  • 5.5.1. IT & Telecom
  • 5.5.2. BFSI
  • 5.5.3. Healthcare
  • 5.5.4. Energy & Utilities
  • 5.5.5. Others(Government, Education, Manufacturing, etc.)
• 5.6. By Region (USD)
  • 5.6.1. North America
  • 5.6.2. Europe
  • 5.6.3. Asia Pacific
  • 5.6.4. Middle East & Africa
  • 5.6.5. South America

6. North America AI-enabled Testing Market Size Estimates and Forecasts, By Segments, 2021-2034

• 6.1. Key Findings
• 6.2. By Deployment (USD)
  • 6.2.1. Cloud
  • 6.2.2. On-premise
• 6.3. By Application (USD)
  • 6.3.1. Web-based
  • 6.3.2. Mobile-based
• 6.4. By Technology (USD)
  • 6.4.1. Machine Learning
  • 6.4.2. NLP (Natural Language Processing)
  • 6.4.3. Computer Vision
  • 6.4.4. MBTA (Model-based test automation)
  • 6.4.5. Others
• 6.5. By Industry (USD)
  • 6.5.1. IT & Telecom
  • 6.5.2. BFSI
  • 6.5.3. Healthcare
  • 6.5.4. Energy & Utilities
  • 6.5.5. Others
• 6.6. By Country (USD)
  • 6.6.1. United States
    • 6.6.1.1. By Industry
  • 6.6.2. Canada
    • 6.6.2.1. By Industry
  • 6.6.3. Mexico
    • 6.6.3.1. By Industry

7. Europe AI-enabled Testing Market Size Estimates and Forecasts, By Segments, 2021-2034

• 7.1. Key Findings
• 7.2. By Deployment (USD)
  • 7.2.1. Cloud
  • 7.2.2. On-premise
• 7.3. By Application (USD)
  • 7.3.1. Web-based
  • 7.3.2. Mobile-based
• 7.4. By Technology (USD)
  • 7.4.1. Machine Learning
  • 7.4.2. NLP (Natural Language Processing)
  • 7.4.3. Computer Vision
  • 7.4.4. MBTA (Model-based test automation)
  • 7.4.5. Others
• 7.5. By Industry (USD)
  • 7.5.1. IT & Telecom
  • 7.5.2. BFSI
  • 7.5.3. Healthcare
  • 7.5.4. Energy & Utilities
  • 7.5.5. Others
• 7.6. By Country (USD)
  • 7.6.1. United Kingdom
    • 7.6.1.1. By Industry
  • 7.6.2. Germany
    • 7.6.2.1. By Industry
  • 7.6.3. France
    • 7.6.3.1. By Industry
  • 7.6.4. Italy
    • 7.6.4.1. By Industry
  • 7.6.5. Spain
    • 7.6.5.1. By Industry
  • 7.6.6. Russia
    • 7.6.6.1. By Industry
  • 7.6.7. Benelux
    • 7.6.7.1. By Industry
  • 7.6.8. Nordics
    • 7.6.8.1. By Industry
  • 7.6.9. Rest of Europe

8. Asia Pacific AI-enabled Testing Market Size Estimates and Forecasts, By Segments, 2021-2034

• 8.1. Key Findings
• 8.2. By Deployment (USD)
  • 8.2.1. Cloud
  • 8.2.2. On-premise
• 8.3. By Application (USD)
  • 8.3.1. Web-based
  • 8.3.2. Mobile-based
• 8.4. By Technology (USD)
  • 8.4.1. Machine Learning
  • 8.4.2. NLP (Natural Language Processing)
  • 8.4.3. Computer Vision
  • 8.4.4. MBTA (Model-based test automation)
  • 8.4.5. Others
• 8.5. By Industry (USD)
  • 8.5.1. IT & Telecom
  • 8.5.2. BFSI
  • 8.5.3. Healthcare
  • 8.5.4. Energy & Utilities
  • 8.5.5. Others
• 8.6. By Country (USD)
  • 8.6.1. China
    • 8.6.1.1. By Industry
  • 8.6.2. India
    • 8.6.2.1. By Industry
  • 8.6.3. Japan
    • 8.6.3.1. By Industry
  • 8.6.4. South Korea
    • 8.6.4.1. By Industry
  • 8.6.5. ASEAN
    • 8.6.5.1. By Industry
  • 8.6.6. Oceania
    • 8.6.6.1. By Industry
  • 8.6.7. Rest of Asia Pacific

9. Middle East & Africa AI-enabled Testing Market Size Estimates and Forecasts, By Segments, 2021-2034

• 9.1. Key Findings
• 9.2. By Deployment (USD)
  • 9.2.1. Cloud
  • 9.2.2. On-premise
• 9.3. By Application (USD)
  • 9.3.1. Web-based
  • 9.3.2. Mobile-based
• 9.4. By Technology (USD)
  • 9.4.1. Machine Learning
  • 9.4.2. NLP (Natural Language Processing)
  • 9.4.3. Computer Vision
  • 9.4.4. MBTA (Model-based test automation)
  • 9.4.5. Others
• 9.5. By Industry (USD)
  • 9.5.1. IT & Telecom
  • 9.5.2. BFSI
  • 9.5.3. Healthcare
  • 9.5.4. Energy & Utilities
  • 9.5.5. Others
• 9.6. By Country (USD)
  • 9.6.1. Turkey
    • 9.6.1.1. By Industry
  • 9.6.2. Israel
    • 9.6.2.1. By Industry
  • 9.6.3. GCC
    • 9.6.3.1. By Industry
  • 9.6.4. North Africa
    • 9.6.4.1. By Industry
  • 9.6.5. South Africa
    • 9.6.5.1. By Industry
  • 9.6.6. Rest of MEA

10. South America AI-enabled Testing Market Size Estimates and Forecasts, By Segments, 2021-2034

• 10.1. Key Findings
• 10.2. By Deployment (USD)
  • 10.2.1. Cloud
  • 10.2.2. On-premise
• 10.3. By Application (USD)
  • 10.3.1. Web-based
  • 10.3.2. Mobile-based
• 10.4. By Technology (USD)
  • 10.4.1. Machine Learning
  • 10.4.2. NLP (Natural Language Processing)
  • 10.4.3. Computer Vision
  • 10.4.4. MBTA (Model-based test automation)
  • 10.4.5. Others
• 10.5. By Industry (USD)
  • 10.5.1. IT & Telecom
  • 10.5.2. BFSI
  • 10.5.3. Healthcare
  • 10.5.4. Energy & Utilities
  • 10.5.5. Others
• 10.6. By Country (USD)
  • 10.6.1. Brazil
    • 10.6.1.1. By Industry
  • 10.6.2. Argentina
    • 10.6.2.1. By Industry
  • 10.6.3. Rest of South America

11. Company Profiles for Top 10 Players (Based on data availability in public domain and/or on paid databases)

• 11.1. Functionize, Inc.
  • 11.1.1. Overview
    • 11.1.1.1. Key Management
    • 11.1.1.2. Headquarters
    • 11.1.1.3. Offerings/Business Segments
  • 11.1.2. Key Details (Key details are consolidated data and not product/service specific)
    • 11.1.2.1. Employee Size
    • 11.1.2.2. Past and Current Revenue
    • 11.1.2.3. Geographical Share
    • 11.1.2.4. Business Segment Share
    • 11.1.2.5. Recent Developments
• 11.2. Sauce Labs Inc.
  • 11.2.1. Overview
    • 11.2.1.1. Key Management
    • 11.2.1.2. Headquarters
    • 11.2.1.3. Offerings/Business Segments
  • 11.2.2. Key Details (Key details are consolidated data and not product/service specific)
    • 11.2.2.1. Employee Size
    • 11.2.2.2. Past and Current Revenue
    • 11.2.2.3. Geographical Share
    • 11.2.2.4. Business Segment Share
    • 11.2.2.5. Recent Developments
• 11.3. Tricentis
  • 11.3.1. Overview
    • 11.3.1.1. Key Management
    • 11.3.1.2. Headquarters
    • 11.3.1.3. Offerings/Business Segments
  • 11.3.2. Key Details (Key details are consolidated data and not product/service specific)
    • 11.3.2.1. Employee Size
    • 11.3.2.2. Past and Current Revenue
    • 11.3.2.3. Geographical Share
    • 11.3.2.4. Business Segment Share
    • 11.3.2.5. Recent Developments
• 11.4. Diffblue Ltd.
  • 11.4.1. Overview
    • 11.4.1.1. Key Management
    • 11.4.1.2. Headquarters
    • 11.4.1.3. Offerings/Business Segments
  • 11.4.2. Key Details (Key details are consolidated data and not product/service specific)
    • 11.4.2.1. Employee Size
    • 11.4.2.2. Past and Current Revenue
    • 11.4.2.3. Geographical Share
    • 11.4.2.4. Business Segment Share
    • 11.4.2.5. Recent Developments
• 11.5. Applitools
  • 11.5.1. Overview
    • 11.5.1.1. Key Management
    • 11.5.1.2. Headquarters
    • 11.5.1.3. Offerings/Business Segments
  • 11.5.2. Key Details (Key details are consolidated data and not product/service specific)
    • 11.5.2.1. Employee Size
    • 11.5.2.2. Past and Current Revenue
    • 11.5.2.3. Geographical Share
    • 11.5.2.4. Business Segment Share
    • 11.5.2.5. Recent Developments
• 11.6. mabl Inc.
  • 11.6.1. Overview
    • 11.6.1.1. Key Management
    • 11.6.1.2. Headquarters
    • 11.6.1.3. Offerings/Business Segments
  • 11.6.2. Key Details (Key details are consolidated data and not product/service specific)
    • 11.6.2.1. Employee Size
    • 11.6.2.2. Past and Current Revenue
    • 11.6.2.3. Geographical Share
    • 11.6.2.4. Business Segment Share
    • 11.6.2.5. Recent Developments
• 11.7. UBS Hainer GmbH
  • 11.7.1. Overview
    • 11.7.1.1. Key Management
    • 11.7.1.2. Headquarters
    • 11.7.1.3. Offerings/Business Segments
  • 11.7.2. Key Details (Key details are consolidated data and not product/service specific)
    • 11.7.2.1. Employee Size
    • 11.7.2.2. Past and Current Revenue
    • 11.7.2.3. Geographical Share
    • 11.7.2.4. Business Segment Share
    • 11.7.2.5. Recent Developments
• 11.8. testim
  • 11.8.1. Overview
    • 11.8.1.1. Key Management
    • 11.8.1.2. Headquarters
    • 11.8.1.3. Offerings/Business Segments
  • 11.8.2. Key Details (Key details are consolidated data and not product/service specific)
    • 11.8.2.1. Employee Size
    • 11.8.2.2. Past and Current Revenue
    • 11.8.2.3. Geographical Share
    • 11.8.2.4. Business Segment Share
    • 11.8.2.5. Recent Developments
• 11.9. Perforce Software, Inc.
  • 11.9.1. Overview
    • 11.9.1.1. Key Management
    • 11.9.1.2. Headquarters
    • 11.9.1.3. Offerings/Business Segments
  • 11.9.2. Key Details (Key details are consolidated data and not product/service specific)
    • 11.9.2.1. Employee Size
    • 11.9.2.2. Past and Current Revenue
    • 11.9.2.3. Geographical Share
    • 11.9.2.4. Business Segment Share
    • 11.9.2.5. Recent Developments
• 11.10. Open Text
  • 11.10.1. Overview
    • 11.10.1.1. Key Management
    • 11.10.1.2. Headquarters
    • 11.10.1.3. Offerings/Business Segments
  • 11.10.2. Key Details (Key details are consolidated data and not product/service specific)
    • 11.10.2.1. Employee Size
    • 11.10.2.2. Past and Current Revenue
    • 11.10.2.3. Geographical Share
    • 11.10.2.4. Business Segment Share
    • 11.10.2.5. Recent Developments

12. Key Takeaways