New Quality Engineering Services 2026 RadarView™ evaluates 51 providers as generative AI and autonomous systems reshape software testing, quality assurance, and enterprise delivery models.
LOS ANGELES, CA – October 2026
As generative AI and agentic technologies accelerate software development, enterprises are facing growing pressure to ensure the quality, security, and reliability of increasingly complex applications. New research from Avasant reveals an 11% increase in demand for quality engineering (QE) services as of June 2026, driven by the widening gap between AI-accelerated software development and traditional testing capabilities.
The findings are highlighted in Avasant’s Quality Engineering Services 2026 RadarView™ and companion Market Insights™ report, which examine how AI is transforming enterprise quality engineering strategies, service delivery models, and the competitive landscape. The research evaluates 51 service providers, recognizing 32 for their practice maturity and future-proofing capabilities.
AI is transforming the economics and complexity of quality engineering
As AI-generated code, autonomous agents, and increasingly frequent software releases become integral to enterprise technology environments, traditional quality assurance approaches are struggling to keep pace. Enterprises must now address two simultaneous priorities: leveraging AI to improve testing productivity while developing new assurance capabilities to validate AI-powered applications and autonomous systems.
The research identifies several key market developments:
- Quality engineering demand is accelerating. AI-driven increases in code generation, development velocity, and release frequency are contributing to an 11% increase in QE services demand as of June 2026, as organizations seek to close the gap between development speed and quality assurance capacity.
- Generative AI is delivering significant productivity improvements. Service providers report productivity gains ranging from 25% to 70% across quality engineering activities, demonstrating AI’s potential to transform testing efficiency and delivery models.
- AI assurance is expanding the quality engineering mandate. Enterprises are extending traditional software validation to encompass AI model accuracy, safety, resilience, explainability, regulatory compliance, and business outcomes, particularly as autonomous and agentic applications become more prevalent.
- Human and AI collaboration is reshaping delivery models. Rather than adopting fully automated testing universally, enterprises are increasingly combining human-led, hybrid, and AI-led execution, determining the appropriate level of human oversight based on application complexity, operational risk, and automation maturity.
- Financial services continues to lead demand. Banking, financial services, and insurance (BFSI) accounts for approximately two in five quality engineering services deals, followed by high-tech, healthcare and life sciences, and retail and consumer packaged goods, where industry-specific requirements are driving demand for specialized testing capabilities.
“The rise of agentic development is creating a new quality challenge: enterprises must validate not only software, but increasingly autonomous systems,” said Abhishek Mukherjee, Research Leader at Avasant. “This is driving demand for specialized QE capabilities spanning accuracy, resilience, safety, and governance.”
A new model for quality assurance in the AI era
The research points to a fundamental shift in how enterprises approach software quality. As AI becomes embedded throughout the software development life cycle, quality engineering is evolving from a primarily testing-focused function into a broader discipline responsible for validating the performance, reliability, and responsible operation of intelligent systems.
This shift is also influencing service provider investment priorities. More than 60% of planned quality engineering practice investments are directed toward asset and human capital development over the coming year, as providers expand automation platforms, specialized expertise, and AI-enabled testing capabilities.
“QE delivery is becoming increasingly dynamic, with human-led, hybrid, and AI-led models operating together,” said Premal Shah, Principal Analyst at Avasant. “Enterprises are selectively applying automation based on risk, complexity, and maturity while keeping human oversight where it matters most.”
Avasant evaluates 51 quality engineering service providers
The Quality Engineering Services 2026 RadarView™ evaluates 51 service providers across two dimensions: practice maturity and future-proofing. Of these, 32 providers were recognized across five categories: Leaders, Innovators, Disruptors, Challengers, and Tech Pioneers.
The assessment examines providers’ service capabilities, intellectual property, innovation investments, partnerships, and experience supporting enterprise quality engineering transformation.
Together with the companion Market Insights™ report, the research provides enterprise decision-makers with an independent perspective on emerging QE trends, evolving service delivery models, and the capabilities required to support AI-enabled software development.
Read the research:
Quality Engineering Services 2026 RadarView™
Quality Engineering Services 2026 Market Insights™
Media Contact
Shael Roopchand
Senior Director, Corporate Strategy
Avasant
Email: shael.roopchand@avasant.com
www.avasant.com