Key Highlights:
1. Gen AI Integration - Organizations are actively integrating/planning Gen AI into Quality Engineering processes, with a focus on test automation, data analysis, and eventually into defect prediction.
2. Intelligent Product Validation - Validating intelligent and connected products is becoming increasingly important, requiring specialized testing approaches and skills.
3. Prioritizing Data Quality - Importance of data quality is still underestimated by many organizations, thus, posing challenges for AI implementation and overall IT efficiency.
4. Sustainability Focus - Organizations are actively working to integrate sustainability into Quality Engineering, including defining Green IT KPIs, measuring environmental impact, and promoting sustainable testing practices.
5. Evolving Skillsets - Skillset of Quality Engineers continues to evolve, with an increased emphasis on data analytics, AI/Gen AI expertise, and product engineering knowledge.
Report is available here.
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