Nearly every company 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 that experience to deploy AI.
Caterpillar’s push into the autonomous space started with mining, where labor shortages and hazardous conditions make automation particularly valuable. Today, it sells automated haul trucks, drilling equipment, underground loaders, dozers, and remote-controlled construction equipment. It also offers a software command center, fleet management, and 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 during a fireside chat at the Ai4 conference in Las Vegas earlier this month.
Expanding AI Into the Field
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 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. And like nearly every other large enterprise, Caterpillar is deploying AI across its business operations and software development pipeline. “We use AI agents to modernize legacy code, generate and test new software, and identify defects earlier,” Mineart said.
Workflow Integration Is the Hard Part
Mineart is quick to point out that building the technology is only part of the challenge — deploying an autonomous machine is not the same as transforming a site to use AI. Companies also have to rethink how people work alongside the technology and how existing processes need to change.
“The hard part about autonomy and about physical AI is incorporating that technology into the customer jobsite and into the workflows,” she said.
Mineart said the company leans on experienced operators to help train AI systems, leveraging institutional knowledge built over decades. As machines become more autonomous, some operators may shift from controlling a single machine to overseeing multiple machines from a remote command center.
A $100 Million Workforce Investment
That transition is creating a new challenge for Caterpillar: retraining its 118,000 employees. Mineart said the company plans to spend $100 million over the next five years to train its workforce in AI, autonomy, and robotics.
That investment coincides with a broader boom in AI infrastructure that is already benefiting Caterpillar’s bottom line. The company’s quarterly revenue reached an all-time high of $20.5 billion in the second quarter, driven in part by strong demand for power-generation equipment used in data centers. Its power-generation division saw sales spike 72% to $3.10 billion, and CEO Joe Creed said that “no one is slowing down” when it comes to demand for cloud computing and generative AI infrastructure — a trend that positions Caterpillar’s decade of automation experience as a meaningful competitive advantage going forward.
