AI Resilience Report forCrushing, Grinding, and Polishing Machine Setters, Operators, and Tenders

Right now, AI in crushing, grinding, and polishing operations is showing up mostly as an assistant to human operators, not a replacement. The heaviest activity is on the "office" side of the job — the paperwork tasks that ONET flags as most automatable, like recording production data and reading work orders. Big equipment makers are rolling out tools to handle these.

In January, Caterpillar launched its Cat AI Assistant ^[1], which unifies Caterpillar's digital applications and operator data into one experience, utilizing Caterpillar's knowledge base and providing personalized data and insights, enabling faster, smarter decisions, and for operators, provides information in the cab to work smarter and safer without switching screens, returning to the yard or losing focus. On the process side, ABB's new Automation Extended program ^[2] is bringing AI into cement and aggregates control rooms, where automation in the cement industry is on a journey towards more autonomous operations, forming the basis for more advanced decision support for operators including AI capabilities, with the digital environment leveraging artificial intelligence and machine learning for decision support without disturbing proven control structures. PwC's Mine 2026 report ^[3] shows the same trend, noting that productivity surges when companies engineer AI to make routine, high-frequency decisions without human intervention.

But the messy, physical parts of this job — clearing jams, cleaning, hand-tool maintenance — still very much need people.

Adoption is real but uneven. The World Economic Forum's June 2026 framework ^[4] reports that 86% of employers expect AI and information-processing technologies to transform their businesses by 2030, but 63% identify skills gaps as the biggest barrier, and that three in four industrial jobs are expected to evolve over the next decade, with 75% expanding in scope or moving towards higher-value activities. In the aggregates world specifically, adoption is slower than the tech hype suggests.

At the Pit & Quarry Roundtable ^[1], one industry veteran said one of the top 10 U.S. producers is still tracking production using Excel sheets that are emailed and aggregated, showing how antiquated the industry still is when it comes to technology, and another added that there is a misconception that AI can solve any part of a company's day-to-day operations without any human interaction, and there is still work to be done on the front end to feed AI with information. Meanwhile, the U.S. Bureau of Labor Statistics projects ^[5] that overall employment of metal and plastic machine workers will decline 7 percent from 2025 to 2035, though about 78,100 openings are projected each year to replace workers who retire or move to other jobs. The takeaway for young people: workers who learn to team up with AI dashboards, sensors, and predictive-maintenance tools will be the most valuable — human judgment, hands-on troubleshooting, and safety awareness aren't going anywhere.