Are Cage Unloaders at Risk Due to AI?

All material moving workers not listed separately.

The occupation "Material Moving Workers, All Other" is assigned an automation risk of 0.0%. This base risk indicates that, based on current technological capabilities and job analysis, the tasks performed by workers in this category are highly resistant to automation. The reasoning behind this negligible risk lies in the diversity and unpredictability of tasks within this occupation, which are difficult for robots or algorithms to replicate reliably. These workers frequently adapt to changing worksite conditions, handle a wide range of materials, and operate in environments where standardization is challenging. As a result, machines or automated systems cannot yet match the versatility and judgment required for these roles. When examining the tasks within this occupation, there are still some elements that could theoretically be automated. The top three most automatable tasks might include (1) simple transportation of goods from one point to another, (2) repetitive sorting or staging of certain transferable materials, and (3) performing inventory counts using barcode scanners or similar devices. Despite these tasks being the most susceptible to automation, their automation is often limited in practice due to the unstructured settings in which material moving workers operate, further reinforcing the low overall automation risk. Conversely, the top three most resistant tasks are (1) adapting quickly to on-the-fly instructions from supervisors, (2) making context-dependent decisions regarding the safest or most efficient handling of irregularly shaped or hazardous materials, and (3) collaborating with human teams under unpredictable conditions. These resistant tasks depend on complex problem-solving, situational awareness, and a high degree of manual dexterity. Key bottleneck skills include adaptability (high level), physical coordination (high level), and real-time communication (moderate to high level), all of which are difficult for current automation technologies to emulate. The combination of these resistant tasks and required skills underlines why the automation risk for material moving workers remains at 0.0%.