Nearly every company that's trying to deploy artificial intelligence runs into the same problem: it's hard to integrate the tech into everyday operations. Industrial heavyweight Caterpillar has spent decades dealing with a version of that problem in the physical world, and now it's using its experience to deploy AI. Caterpillar's push into the autonomous space started with mining, where labor shortages and hazardous conditions can make automation particularly useful. Today, it sells automated haul trucks, drilling, underground loaders, dozers, remote-controlled construction equipment, and more.
It also offers a software command center, fleet management, and even remote terrain intelligence as part of its autonomous toolkit. “Now we're in this super exciting time where we can take all of that learning from mining and bring it into much more dynamic environments, jobsites, quarries, and construction sites,” the company's CTO, Jaime Mineart, told TechCrunch on the sidelines of the Ai4 conference in Las Vegas earlier this month. The industrial giant is now applying AI more broadly, including in tools used by technicians and its own employees.
One example is the Cat AI Assistant , which lets field technicians standing next to a machine use voice commands to pull up repair procedures, troubleshoot potential problems, and identify parts that may be needed before beginning a repair. Mineart said the tool is now being used by customers, operators and technicians. The assistant draws on Caterpillar's proprietary data, which spans information generated by its connected machines. Mineart said Caterpillar has about 1. 6 million connected assets globally and more than 16 petabytes of structured data.
The company is also using AI to power software for scanning sites and generating digital twins in manufacturing to analyze operations, she said. And like nearly every other company, Caterpillar is using AI across its enterprise operations, as well as for software development. "We use AI agents to modernize legacy code, generate and test new software, and identify defects earlier,” Mineart said. But Mineart is quick to point out that building the technology is only part of the challenge, as deploying an autonomous machine is not the same as transforming a site to use AI.