Caterpillar Turns Mining Automation Expertise Into a Broader AI Strategy

Caterpillar Turns Mining Automation Expertise Into a Broader AI Strategy

Caterpillar is expanding its use of artificial intelligence beyond mining, applying decades of experience with autonomous heavy equipment to products including the Cat AI Assistant, manufacturing digital twins, site-scanning tools and software agents that help update legacy code.

The company’s AI strategy builds on technology first developed for mining operations, where Caterpillar has deployed autonomous haul trucks, drilling systems, loaders and dozers. Chief Technology Officer Jaime Mineart said the company is now adapting that expertise for less controlled settings such as construction sites and quarries. “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,” Mineart said at the Ai4 conference in Las Vegas earlier this month.

Among Caterpillar’s customer-facing AI products is the Cat AI Assistant, which allows technicians working beside a machine to use voice commands to access repair instructions, diagnose issues and locate parts. Mineart said the tool is already being used by customers, operators and technicians.

Caterpillar is supporting those systems with operational data gathered from about 1.6 million connected assets worldwide and more than 16 petabytes of structured information. The company is also using AI to scan work sites and create digital twins that can be used to examine manufacturing operations.

AI is moving into Caterpillar’s software organization as well. Agents are being used to help modernize older code, write and test software and identify defects earlier in development. But Mineart said deploying the technology is only part of the work. Autonomous equipment also changes how employees interact with machines and how jobs are organized at operating sites. “The hard part about autonomy and about physical AI is incorporating that technology into the customer jobsite and into the workflows,” she said.

Caterpillar is drawing on experienced equipment operators to help train its AI systems, using knowledge developed through years of operating machinery in the field. As equipment becomes more autonomous, some workers could shift from directly operating a single machine to supervising several machines remotely.

The company plans to spend $100 million over the next five years to train its 118,000 employees in AI, autonomy and robotics. Caterpillar is making that investment while another part of the AI buildout is already contributing to its financial results. The company reported a record $20.5 billion in sales and revenue for the second quarter of 2026, up 24% from a year earlier.

Its Power & Energy segment generated $8.2 billion in sales, an increase of 17%. Within that business, Power Generation revenue rose 29% to $3.10 billion from $2.41 billion a year earlier. Caterpillar separately reported a 72% increase in Power Generation retail sales, which measures dealer deliveries to customers rather than recognized revenue.

The company also reported adjusted earnings per share of $8.17, up 73%, while its order backlog reached a record $72.1 billion, an increase of 92%. Demand from data centers has been a major contributor to Caterpillar’s power-generation business as companies expand infrastructure for cloud computing and generative AI. Chief Executive Joe Creed said that demand remains strong. “No one is slowing down,” Creed said.

For Caterpillar, the next stage of its AI expansion depends less on introducing a single product than on extending automation across a wider range of operating environments. Its mining systems provide a foundation, but moving autonomous equipment into construction sites and other changing workplaces requires new workflows, worker training and closer coordination between people and machines.

The company is approaching that transition with a combination of proprietary equipment data, existing autonomous systems and a large workforce training program as it pushes AI deeper into both its machinery and internal operations.

This analysis is based on reporting from BigGo Finance.

Image courtesy of ua.news.

This article was generated with AI assistance and reviewed for accuracy and quality.

Updated Aug 31, 2026

About this article: This article was generated with AI assistance and reviewed by our editorial team to ensure it follows our editorial standards for accuracy and independence. We maintain strict fact-checking protocols and cite all sources.

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