Your CEO Sees 5x. Your Engineers See a Longer Review Queue.

A growing disconnect exists between executive expectations and engineering reality regarding AI adoption. While C-suite leaders report 5x productivity gains from AI super-users, engineering teams report increased workloads, specifically citing longer code review queues and organizational inefficiencies. Data from Atlassian, Harness, and other industry reports highlight that while AI accelerates the 16% of time spent coding, it does little to alleviate the 84% of time consumed by meetings, context switching, and administrative tasks. Furthermore, many executives admit their AI strategies are performative due to pressure to show ROI. The article argues that this gap stems from differing metrics: leadership tracks output speed, while engineers track long-term stability and technical debt. To bridge this divide, experts suggest that organizations must move beyond vanity metrics, ensure transparency in how AI data is used for performance reviews, and prioritize developer feedback to address actual pain points rather than just theoretical productivity gains.