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Hello All,

Within our wholesale drug distribution warehouses, a key robotic application is the deployment of autonomous mobile robots $($AMRs$)$ for order picking and material transport. These robots navigate complex layouts, retrieve drugs and other items from storage, and deliver them to packaging and shipping areas. Their integrated sensor systems and advanced navigation algorithms allow them to operate efficiently while sharing space with human workers, reducing processing times and order fulfillment errors $($Sharda$,$ Delen, & Turban, $2020).$

The selected application falls into the collaborative robot category. Unlike preset robots that strictly follow a fixed routine or remote$-$controlled robots that require constant human oversight, these AMRs are designed to work alongside humans. They adjust their paths dynamically and are programmed with safety features such as obstacle detection and emergency stop functions to ensure they operate harmoniously within human$-$centric environments. The combination of autonomous decision$-$making and real$-$time interaction with human workers makes them exemplary collaborative robots, which align with modern decision$-$support systems enhanced by analytics and AI $($Sharda$,$ Delen, & Turban, $2020).$

However, as these collaborative AMRs assume routine and physically demanding tasks, specific jobs may be at risk of disappearing. Positions that rely heavily on manual order picking, repetitive heavy lifting, and basic material handling could diminish over time as robots take over these labor$-$intensive activities. The reduced need for human involvement in such tasks may eventually lead to a decline in traditional warehouse worker roles based solely on repetitive physical work.

On the other hand, the integration of AMRs is likely to generate new employment opportunities. One category of jobs expected to emerge involves technical roles focused on maintaining, repairing, and programming robotic systems. As these systems become a central part of warehouse operations, skilled technicians and engineers will be needed to ensure their proper functioning and continuous improvement. Additionally, a new category of roles centered on data analysis and operational optimization will likely develop. Professionals in these positions will analyze real$-$time performance data from the robots, allowing managers to fine$-$tune workflows and improve overall efficiency. Furthermore, roles in managing human$-$robot collaboration, such as safety supervision and specialized training for effective interaction with automated systems, will also grow in importance $($Sharda$,$ Delen, & Turban, $2020).$

Additional industry insights reinforce these points. For example, a Reuters $(2024)$ article describes how major retailers' expansion of warehouse robots boosts efficiency and transforms job roles, shifting workers into more technical and supervisory positions. Similarly, an analysis from Ultrand $(2025)$ highlights how robotics is revolutionizing the pharmaceutical supply chain by enhancing accuracy and reducing errors, thereby underscoring the potential for collaborative robots to displace routine manual tasks and create higher$-$skilled jobs.