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The Rise of Generative AI in Quality Engineering: Insights from World Quality Report 2025

In a groundbreaking new report released on November 13, 2025, OpenText Corporation, in collaboration with global technology firm Capgemini, highlights a significant surge in the integration of generative AI within quality engineering practices. The World Quality Report 2025, marking its 17th edition, takes a meticulous look at application quality and testing trends, revealing that while about 90% of organizations are actively embracing generative AI, only 15% have successfully implemented it on an enterprise scale.

Key Findings

The report underscores a widening gap between the growing interest in generative AI and the actual preparedness of quality engineering divisions for effective implementation. Moving from experimental phases to comprehensive integration is proving more complex than previously anticipated, necessitating a cohesive strategy between management and business innovation.

Tal Levi-Joseph, Vice President of Application Delivery Management at OpenText, emphasizes that "quality engineering is being redefined by AI. Maintaining the status quo is no longer an option. Organizations must adopt AI-driven transformation to remain competitive and deliver results with greater confidence rapidly. AI is guiding organizations to extend quality management beyond traditional testing frameworks to encompass the entire software delivery lifecycle."

Mark Buenen, Capgemini’s Global Leader for Quality Engineering & Testing, further asserts, "Comparing annual data from the World Quality Report shows that generative AI in quality engineering is transitioning from initial experimentation to strategic integration. While tech advancements are evident, many organizations still struggle to align generative AI with business objectives. In 2025, there will be increased focus on governance, ROI, and cross-functional impacts. The ongoing challenge is to bridge the generative AI gap and translate investments into measurable value."

Adoption Statistics

The survey conducted for this report reveals the following key statistics:

• - Widespread Adoption: 89% of responding organizations are testing operational workflows using generative AI, with 37% in full production and 52% in trial phases.
• - Scale Barriers: Despite this high interest, only 15% of respondents reported successful enterprise-level implementation, while 43% are still in experimental stages and 30% are limited to specific use cases.
• - Evolving Use Cases: Generative AI is transitioning from output analysis (such as defect analysis and reporting) to optimizing input data, with its integration driven by test case design and requirements refinement.
• - Operational Challenges: Although organizations report an average productivity increase of 19%, about a third have experienced only minor gains, highlighting the need for refined integration strategies.
• - New Barriers: Respondents identified major challenges in 2025, including integration complexities (64%), data privacy concerns (67%), and credibility issues due to hallucinations in AI outputs (60%). These differ from the previous year, where challenges revolved around strategic issues like lack of validation strategies (50%) and insufficient AI/ML expertise (42%).
• - Skill Gaps Persist: Half of respondents noted a lack of AI/ML expertise within their organizations, a figure that remains unchanged from 2024.
• - Lack of Strategic Alignment: Many organizations treat generative AI as a tactical enhancement rather than a strategic driver, resulting in fragmented execution and inadequate funding for initiatives.

Strategic Insights

Tal Levi-Joseph adds, "To unlock the true potential of generative AI in quality engineering, investments in skills, governance, data, and outcome alignment are crucial. While AI amplifies capabilities, it cannot replace them. The organizations that succeed are those that fortify their quality engineering foundations and enhance core competencies such as design, development, and testing with AI."

The report also highlights the emergence of collaborative intelligence, where human expertise and AI capabilities intersect to produce high-quality outcomes. This hybrid approach is critical in balancing the tension between innovation and accountability. While a shift-left approach remains prominent in quality engineering, the rise of shift-right strategies is also evident.

For organizations seeking more in-depth insights, the complete World Quality Report 2025 is available for download at OpenText Resources.

Additional Information

OpenText has recently been recognized as one of the leaders in the 2025 Gartner® Magic Quadrant™ for AI-Augmented Software Testing Tools. For more details, visit their official site.

The World Quality Report 2025 serves as an annual overview of the latest trends, challenges, and future outlooks in quality engineering across various industries. Based on extensive surveys and interviews with industry leaders, it provides crucial insights to better understand the landscape surrounding software quality.

For more about OpenText's DevOps Cloud solutions, visit OpenText's website at OpenText.

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