Recent times saw captivating improvements to artificial intelligence-assisted code completion technology. The precise effect this contributes to conventional software development is an exciting consideration for individuals and corporations seeking modern workflow optimization approaches. A team’s productivity may be defined as the amount of work that can be completed in a certain amount of time. However, determining an exact metric for productivity proves to be a challenging task. To this end, a case study was conducted at a leading automotive organization investigating the effects on software developers who employ GitHub Copilot as part of their daily work. Typical agile working model metrics were evaluated in context of the SPACE framework to devise a means of measuring GitHub Copilot’s impact on developer productivity. Some improvements were observed from the case study across the throughput, cycle time, code quality, defects, and developer satisfaction measures. This ultimately led to an increase in developer productivity.