Quality Engineering/Software Testing: Continuous Testing and AI

Quality Engineering/Software Testing: Continuous Testing and AI

Who is This Market Analysis For?

NelsonHall’s “Quality Engineering: Continuous Testing and AI” report is a comprehensive market assessment report designed for:
• Sourcing managers investigating sourcing developments within software testing services/Quality Assurance/Quality Engineering
• Vendor marketing, sales, and business managers developing strategies to target testing services/QE opportunities
• Financial analysts and investors specializing in the IT services sector.

Key Findings & Highlights

NelsonHall’s market analysis of the quality engineering (QE)/software testing services market consists of 66 pages. The report provides an in-depth understanding of the dynamics at play in QE, and looks specifically at continuous testing, cognitive and QA, UX testing, model-based testing, and cloud testing.

The current global software testing services market size stands at ~$36bn. NelsonHall expects a rebound in 2021 (+4%), led by a catch-up, after a moderate deceleration in 2020 (+2.5%) in testing services spending. This 2020 deceleration was much softer than expected with clients pushing external testing expenses, cloud, and digital projects. Growth in 2022 will slow down somewhat to +3%, impacted by the end of the catch-up effect. Spending will reach $38bn in 2024, representing a +4% CAGR 2020-2025.

The market remains structured around BFSI, which represents ~41% of testing service spending (and 45% including U.S. healthcare payers). The sector, with its large custom applications and regular updates, fits well the traditional multi-year contract model.

Functional testing (including manual activities, automation, COTS, and digital testing) represents ~84% of spending. Specialized services account for the remaining 16%, with non-functional representing 9%.

Scope of the Report

This report examines high-potential testing services offerings, including accepted ones (e.g., continuous testing) with still room for growth, and emerging areas (e.g., infrastructure-as-code).

The quality engineering (QE) offerings covered are:
• Continuous testing
• Application migration to the cloud testing
• Infrastructure as code (IAC) testing
• Model-based testing
• AI-based analytics for more focused testing
• AI-based automation, usually for automating the creation and maintenance of test cases/scripts
• Testing of RPA bots
• Testing of chat- and voice-bots
• Testing of AI models
• Explainable AI
• UX testing across usability, compatibility, accessibility, and content testing
• Application security testing.

It addresses the following questions:
• What is the current and future market for QE/software testing services?
• What are the client segments for software testing services, and their characteristics? What are the drivers, benefits, and inhibitors for each segment?
• What is the size and growth of the software testing services markets by client segment, geography, service line, activity and sector?
• How did spending grow in 2021and how will it increase in 2022 and onward?
• How is the market organized? Who are the main vendors? How can they be assessed and compared? What are vendor challenges and critical success factors by market segment?
• Has continuous testing reached maturity or is there still room for innovation?
• What offerings have high potential?
• How is AI shaping the testing market for bringing test automation and also testing cognitive technologies such as AI models, RPA/business process automation, and virtual assistants
• What is the maturity of application security testing?