Teams of humans and robots have become commonplace in various industrial settings as companies pursue new ways to cut costs and increase efficiency. Although these collaborations have improved operational performance, they are far from realizing their full potential in many cases. This research focuses on such teams in warehouse operations, where robots now routinely work alongside humans. Because the operational circumstances in warehouses can vary significantly, we have developed a framework to support managers in balancing two key dimensions: the level of human expertise and the level of robot autonomy. This matrix roughly categorizes human-robot collaboration (HRC) into four distinct quadrants: Robot-in-lead, Human-in-lead, Elementary HRC, and Advanced HRC. Each category is illustrated with insightful practices in companies such as Amazon, DHL, Zalando, or JD.com, among others. Finally, we present how AI technologies can enhance HRC by considering AI’s five impact areas: Contextualization, Communication, Customization, Task Performance, and Continuous Improvement. Based on comprehensive analysis, our framework aims to help managers configure compelling combinations for enhancing warehouse operations and address evolving market demands.