The global automation testing market size is poised to grow substantially in the near future, driven by increasing digitalization and widespread adoption of advanced technologies including artificial intelligence (AI) and machine learning. A large number of enterprises have already started adopting AI and machine learning concepts to improve the use and development of applications. With constant technological developments and an increased demand for new, more advanced applications, the automation testing landscape is evolving rapidly.

Rapid digitalization worldwide has substantially increased the number of applications used by enterprises, creating a massive demand for quality automation testing solutions. The emergence of new techniques driven by ongoing technological advances will help improve the quality of testing and ensure deliver of seamless applications for an enhanced user experience.

Based on the end point interface, the industry is segmented into mobile, desktop, web, cloud, and embedded software. Desktop interface accounted for over 10% revenue share of automation testing industry in 2019 and will continue to witness a notable adoption by 2026. These trends will be mainly influenced by increasing digitalization in the industrial sector. A wide variety of testing services are required to ensure reliable and optimized automation of industrial operations.

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In terms of the applications, the market is classified into IT & telecom, retail, manufacturing, BFSI, healthcare, automotive, smart consumer devices, government & public sector, transportation & logistics, medical devices, and others. The automotive sector captured more than 5% share of automation testing market in terms of revenue during 2019 and is projected to experience healthy growth by 2026. The need for testing solutions will be largely driven by growing adoption of advanced systems such as ADAS and in-vehicle infotainment into vehicles.

The number of electronics components as well as the level of software used in vehicles has increased significantly over the past several years. As a result, the need for automation testing in the industry is greater than ever. AI based solutions are also being utilized in every stage of development, from manufacturing to modelling and testing.

Advanced systems such as automotive manufacturing bots must be tested thoroughly to help ensure that they meet latest safety and security standards. In addition to AI, machine learning is also playing a crucial role in automating the testing of complex software stacks. Growing developments in electric vehicles and autonomous vehicles is likely to boost the technology adoption in the auto industry.

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Considering the regional landscape, Latin America held nearly 10% revenue share of global automation testing industry in 2019 and will record substantial gains in the future. The regional technology adoption can be associated with increasing investments in development of the IT sector. In addition, rapid digitalization and increasing adoption of different applications among enterprises will certainly complement the regional outlook.

Table of Contents

Chapter 1 Methodology and Scope

• 1.1 Scope & definition
• 1.2 Methodology & forecast parameter
• 1.3 Data Sources
  • 1.3.1 Primary
  • 1.3.2 Secondary

Chapter 2 Executive Summary

• 2.1 Automation testing industry 360 degree synopsis, 2015-2026
  • 2.1.1 Business trends
  • 2.1.2 Regional trends
  • 2.1.3 Component trends
    • 2.1.3.1 Testing type trends
    • 2.1.3.2 Service trends
  • 2.1.4 End point interface trends
  • 2.1.5 Application trends

Chapter 3 Automation testing Industry Insights

• 3.1 Industry segmentation
• 3.2 Industry landscape, 2015-2026
  • 3.2.1 Automation testing tools and platforms
    • 3.2.1.1 Selenium
    • 3.2.1.2 Testing Whiz
    • 3.2.1.3 Ranorex
    • 3.2.1.4 HPE Unified Functional Testing
    • 3.2.1.5 TestComplete
    • 3.2.1.6 Sahi
    • 3.2.1.7 Watir
    • 3.2.1.8 Telerik Test Studio
    • 3.2.1.9 Katalon Studio
    • 3.2.1.10 Tosca Test Suite
  • 3.2.2 Wireless automation testing industry overview
    • 3.2.2.1 Wi-Fi
    • 3.2.2.2 Bluetooth
    • 3.2.2.3 IoT
• 3.3 Impact analysis of corona virus (COVID-19) pandemic on automation testing market
  • 3.3.1 Impact by region
    • 3.3.1.1 North America
    • 3.3.1.2 Europe
    • 3.3.1.3 Asia Pacific
    • 3.3.1.4 Latin America
    • 3.3.1.5 MEA
  • 3.3.2 Impact on industry value chain
  • 3.3.3 Impact on competitive landscape
• 3.4 Industry ecosystem analysis
• 3.5 Technology & innovation landscape
• 3.6 Regulatory landscape
  • 3.6.1 North America
  • 3.6.2 Europe
  • 3.6.3 Asia Pacific
  • 3.6.4 Latin America
  • 3.6.5 MEA
• 3.7 Industry impact forces
  • 3.7.1 Growth drivers
    • 3.7.1.1 Growing adoption of AI and ML in automation testing
    • 3.7.1.2 Increasing adoption of DevOps methodology
    • 3.7.1.3 Rising adoption of agile development environment for Quality Assurance and testing
    • 3.7.1.4 Increase in consumption of mobile-based applications
    • 3.7.1.5 Growing digitalization in developing economies
  • 3.7.2 Industry pitfalls and challenges
    • 3.7.2.1 Lack of skilled professionals
    • 3.7.2.2 High implementation cost prevailing manual testing over automation testing
• 3.8 Growth potential analysis
• 3.9 Porter's analysis
  • 3.9.1 Industry rivalry
  • 3.9.2 Threat of new entrants
  • 3.9.3 Buyer power
  • 3.9.4 Supplier power
  • 3.9.5 Threat of substitutes
• 3.10 PESTEL analysis