World Quality Report 2024 shows 68% of Organizations Now Utilizing Gen AI to Advance Quality Engineering

Developer productivity and quality engineering has passed the tipping point of adopting generative AI to drive business success, says the 16^th edition of the report

OpenText, in collaboration with Capgemini and Sogeti (part of the Capgemini Group), today announced the findings of the 16^th edition of the World Quality Report, “New Futures in Focus.” The report reveals significant developments in Quality Engineering (QE), with a growing emphasis on the integration of Generative AI (Gen AI) and a notable shift in the skills required to excel in Agile development environments.

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The World Quality Report 2024 surveyed organizations across various industries to capture the current trends in software engineering and developer best practices. Quality Engineering that was once defined as testing human-written software has now evolved with AI generated code. From the volume of code and test scripts that need to be generated, to how software chains have to be tested end-to-end, the need for redefinition of Quality Engineering is reshaping the focus and strategy of many testing and software engineering teams. The report emphasizes the increasing adoption of Gen AI and its impact on test automation, alongside the critical need for organizations to better align QE metrics with business outcomes to showcase its strategic value.

Key Findings from the Report Include:

• Gen AI Dominates Quality Engineering Trends:
  The report shows 68% of organizations are either actively utilizing Gen AI (34%) or have developed roadmaps following successful pilot implementations (34%). Test automation is the leading area where Gen AI is making an impact, with 72% of respondents reporting faster automation processes as a result of Gen AI integration.
  
  
• Upskilling Remains Crucial:
  While 82% of organizations report having dedicated learning pathways for their QE teams, only 50% actively track the effectiveness of these programs. The report stresses the importance of continuous learning, especially in skills such as Gen AI, Agile integration and cross-functional collaboration. 
  
  
• Automation and Legacy System Challenges Persist:
  The report also uncovers the challenges many organizations face in automating their testing environments. A lack of comprehensive test automation strategies and reliance on legacy systems were identified by 57% and 64% of respondents, respectively, as key barriers to advancing automation efforts.
  
  
• Sustainability and Green IT Priorities Lag Behind:
  Despite widespread recognition of sustainability as a top priority, the report finds that only 25% of organizations are measuring the environmental impact of their overall IT development, while 44% are tracking the impact of testing activities. Furthermore, only 34% of respondents are implementing efficient Quality Engineering practices to drive sustainability. The report calls for organizations to adopt comprehensive Green IT strategies and improve environmental impact measurement across the entire software development lifecycle.

“The insights from this year’s World Quality Report emphasize the growing role of AI and emerging technology methodologies in Quality Engineering, but they also reveal a clear need for organizations to recognize and communicate QE’s strategic value,” said Muhi Majzoub, EVP and Chief Product Officer at OpenText. “As technology evolves, OpenText is dedicated to helping organizations integrate advanced software lifecycle management solutions with Gen AI while ensuring that Quality Engineering remains at the forefront of driving business success.”

“Gen AI tools and solutions are clearly gaining adoption by quality engineers to assist them in their function and focus on higher-value-added tasks,” said Mark Buenen, Global Leader, Quality Engineering and Testing at Sogeti. “This year’s World Quality Report shows a striking shift with a large majority of respondents who are either actively using Gen AI in their QE processes or crafting implementation roadmaps. Beyond its proven impact on coding efficiency and quality, Gen AI has the potential to further accelerate the transformation of quality engineering and create new value for both clients and end users.”

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