Material recording clerks

1,300,800 jobs in the US · AI exposure 7/10 · AI opportunity 4/10

What AI will never replace

Physically inspecting a shipment for damage, verifying that what's actually on the pallet matches the bill of lading, and flagging discrepancies that don't show up in the scan require eyes and hands on the goods. Resolving disputes with vendors when inventory counts don't match—calling, negotiating credits, escalating—depends on human communication and relationship management. In fast-moving warehouse environments, adapting to last-minute schedule changes and coordinating with truck drivers in person keeps operations running when systems lag behind reality.

AI exposure: 7/10

This occupation is highly exposed because its core functions—tracking data, scheduling, and inventory reporting—are digital information-processing tasks that AI and automated systems excel at. While some physical presence is required to inspect goods or handle packages, the rapid integration of AI-driven logistics software, RFID technology, and computer vision for quality control is already leading to a projected decline in employment.

AI advantage: 7/10

AI significantly enhances core tasks like production scheduling, inventory forecasting, and vendor communication, creating a major gap between manual record-keepers and AI-augmented clerks. While some physical inspection and handling remain, AI tools can automate complex data entry, report generation, and logistics optimization that previously required significant manual effort. The projected job decline highlights that those who do not adopt these efficiency-boosting technologies are at high risk of being replaced by automated systems.

Job growth outlook: 1/10

AI and computer vision directly automate the core tasks of this role, such as defect inspection, inventory counting, and shipment tracking, leading to a projected decline in employment. While AI improves supply chain efficiency, it primarily replaces the need for human recordkeepers through automated sensors, RFID, and predictive logistics software.

Career details

  • Typical education: High school diploma or equivalent
  • Median annual pay: $46,120
  • 10-year outlook: Decline