GitLab recently hosted a virtual event, GitLab Transcend, emphasizing the role of agentic AI in software delivery. Over the last decade, DevOps successfully integrated speed and quality into software development practices, fostering better automation, continuous quality management, and shared accountability. However, the current AI frenzy threatens this balance. A report from Sauce Labs highlights that 95% of companies experienced setbacks in their AI initiatives, revealing a lack of skilled testers and proper tools. Eighty-two percent of companies admit they are unprepared to manage this new technology, resulting in a worrying disconnect between innovation and quality assurance. Leadership's understanding of software testing is alarmingly low, with 61% of surveyed professionals stating their senior management lacks fundamental knowledge in this area. This ignorance leads to poor quality practices being overlooked, and 60% of leaders say that blame for AI errors falls on the employees executing AI decisions rather than the developers. Many leaders, instead of committing resources to improve quality, express indifference, citing budget constraints or a lack of awareness. The culture within these organizations fosters fear of repercussions for mistakes, which further complicates the path to innovation. Divided nearly evenly, companies are at a crossroads regarding AI initiatives. About 48% want to intensify their AI investments, while 47% plan to slow down and reassess their strategies. The report indicates a need for a balanced approach that honors the principles of speed and quality. Seventy-two percent of leaders believe fully autonomous testing is achievable by 2027, but to reach that goal, a supportive quality framework is essential. The focus should shift from assigning blame to creating an environment where teams can succeed, reinforcing the foundational lessons learned over the past decade.