The World Quality Report 2025: Adapting to Emerging Worlds offers a compelling look into the evolving landscape of quality engineering (QE). Now in its 17th year, the report captures the pulse of a sector undergoing rapid transformation, driven by the rise of AI-augmented DevOps and the growing influence of generative AI (Gen AI). This evolution is centered around embedding quality across the entire software development lifecycle (SDLC), from design and development to testing and deployment.

The gen AI adoption paradox: high interest, low scale

This year’s findings reveal a striking paradox: While 89% of organizations surveyed are actively piloting or deploying Gen AI in their QE practices, only 15% have achieved enterprise-scale implementation. The initial surge of enthusiasm has given way to a more cautious, strategic recalibration as organizations are realizing that scaling AI requires more than technology. It demands AI governance, skill and trust.

How AI is transforming the software development lifecycle

One of the most notable shifts is the move from using AI to analyze outputs, such as defect reports and test logs, to shaping inputs. Test case design and requirements refinement now lead Gen AI adoption, signaling a deeper integration into the SDLC. This evolution is reshaping DevOps, where AI agents are not just supporting workflows but are actively augmenting them. It is also impacting how development teams approach security.

Barriers slowing enterprise-scale AI adoption

However, the journey is far from smooth. The report identifies several key challenges:

• Integration complexity: 64% responded that AI tools often clash with legacy QE workflows, inhibiting adoption.
• Data privacy risks: 67% of respondents noted serious concerns related to feeding sensitive test data into AI systems.
• Skill gaps: 50% of quality engineering teams reported the lack of foundational AI/ML knowledge is limiting their ability to validate and challenge AI outputs.
• Trust and reliability concerns: 60% said hallucinations and explainability issues are undermining confidence in AI-generated results.

These challenges underscore a critical truth: AI amplifies capability but cannot substitute for it. Success hinges on strengthening QE fundamentals: clear ownership, strategic alignment and measurable outcomes.

The role of collaborative intelligence

The report also explores the concept of collaborative intelligence, where human expertise and AI capabilities converge. This hybrid model is the synthesis of human expertise and AI capabilities, and it is proving essential as organizations balance innovation with accountability. In short, it’s not about replacing testers but empowering them to work smarter and more strategically.

To move from experimentation to transformation, the report offers a set of actionable recommendations:

• Invest in structured AI training: Upskill quality engineering professionals to critically evaluate AI outputs and design effective prompts.
• Establish clear AI ownership: Create dedicated roles with accountability for AI initiatives to avoid fragmented execution.
• Align QE metrics with business outcomes: Move beyond efficiency to demonstrate impact on revenue, risk reduction and customer satisfaction.
• Strengthen data governance: Ensure high-quality, secure inputs for AI systems to prevent flawed outputs and compliance breaches.
• Bridge the pilot-to-scale gap: Connect operational enthusiasm with strategic priorities to unlock enterprise-wide adoption.

The road ahead for AI-driven quality engineering

The 2025 World Quality Report makes it clear: The future of QE lies in AI-augmented DevOps, but only if organizations are willing to recalibrate their strategies. The road ahead demands a shift in mindset from tactical experimentation to strategic enablement. By embracing AI’s potential while reinforcing the pillars of trust, governance, and collaboration, enterprises can unlock new levels of innovation and resilience.

At OpenText, we believe that quality is not just a technical function. It is a strategic enabler of business growth. As the industry adapts to emerging worlds, we remain committed to supporting organizations on their journey toward intelligent, outcome-driven quality engineering.

Get your copy of World Quality Report 2025: Adapting to Emerging Worlds today!

Note: The World Quality Report 2025: Adapting to Emerging Worlds was sponsored by OpenText in collaboration with Capgemini and Sogeti.

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