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Nearly every company that\u2019s trying to deploy artificial intelligence runs into the same problem: it\u2019s 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\u2019s using its experience to deploy AI.<\/p>\n
Caterpillar\u2019s 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.<\/p>\n
\u201cNow we\u2019re 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,\u201d the company\u2019s CTO, Jaime Mineart, told TechCrunch on the sidelines of the Ai4 conference in Las Vegas earlier this month.<\/p>\n
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<\/a>, 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.<\/p>\n The assistant draws on Caterpillar\u2019s 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.<\/p>\n 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. \u201cWe use AI agents to modernize legacy code, generate and test new software, and identify defects earlier,\u201d Mineart said.<\/p>\n 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. Companies also have to rethink how people work alongside the technology and how existing processes need to change.<\/p>\n \u201cThe hard part about autonomy and about physical AI is incorporating that technology into the customer jobsite and into the workflows,\u201d she said.<\/p>\n Mineart said the company leans on experienced operators to help train AI systems, leveraging institutional knowledge built over decades. And as machines become more autonomous, some operators may shift from controlling a single machine to overseeing multiple machines from a remote command center.<\/p>\n That transition, however, is creating a new challenge for Caterpillar: training its 118,000 employees. Mineart said the company plans to spend $100 million over the next five years<\/a> to train its workforce in AI, autonomy and robotics.<\/p>\n That investment is likely being put towards helping the company make the most of the broader boom in AI infrastructure, which is already helping its top-line. Caterpillar\u2019s quarterly revenue reached an all-time high of $20.5 billion<\/a> in the second quarter, helped 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 \u201cno one is slowing down\u201d when it comes to demand for cloud computing and generative AI infrastructure.<\/p>\n<\/div>\n When you purchase through links in our articles, we may earn a small commission<\/a>. This doesn\u2019t affect our editorial independence.<\/em><\/p>\n