Artificial Intelligence in Industrial Companies
We analyzed the enterprise AI use cases of 10 industrial companies to understand trends, impact, and insights.
Industrial companies' adoption of AI
Overview
Since 2018, John Deere has progressively integrated advanced AI technologies such as machine learning, computer vision, and autonomous systems into agricultural machinery, exemplified by products like the 'See & Spray' technology and fully autonomous tractors showcased at CES events, driving precision agriculture innovations.
General Electric (GE) has progressively expanded its AI integration across multiple industrial sectors since 2016, evolving from building an 'AI workforce' to deploying advanced AI-driven solutions in aerospace, healthcare, and energy.
Since 2018, 3M has increasingly integrated AI and machine learning across multiple business areas including healthcare, manufacturing, and materials science, progressing from initial platform adoption (C3.ai) to extensive deployments in conversational AI, supply chain optimization, and data center infrastructure innovation.
Honeywell has aggressively integrated AI across multiple industrial sectors including aerospace, retail, manufacturing, and building management from late 2023 through early 2026, unveiling AI-powered platforms such as Guided Work Solutions, Forge Performance+ for Aerospace, and TrackWise for life sciences manufacturing.
Since 2018, Caterpillar has steadily integrated AI and machine learning into its operations, starting with data management systems and predictive analytics for equipment performance, progressing to advanced autonomous capabilities and AI-powered customer and operational solutions by 2026.
Emerson Electric has steadily expanded and integrated AI-driven automation solutions, especially in the power and water industries, launching key products such as Ovation 4.0 platform and AI-enabled Virtual Advisors by Q3 2025, demonstrating increasing AI adoption with strategic collaborations such as with TotalEnergies and significant investments in AI research with the University of Texas at Austin.
Parker-Hannifin has consistently integrated AI technologies into its operations since Q1 2022, rapidly expanding from strategic partnerships (e.g., with Camgian) to internal applications enhancing manufacturing, supply chain forecasting, and predictive maintenance.
Illinois Tool Works (ITW) has progressively integrated AI technologies primarily in manufacturing through predictive maintenance and decentralized AI strategies, focusing on operational efficiency and innovation.
Eaton has significantly expanded its role in AI infrastructure from 2023 to early 2026, focusing on power management solutions critical for AI data centers and edge computing through partnerships (notably with NVIDIA and Siemens Energy) and advanced firmware solutions addressing AI power load spikes.
Rockwell Automation has progressively expanded its AI capabilities from initial anomaly detection with FactoryTalk Analytics LogixAI in 2019 to advanced generative AI and edge AI models by 2025, partnering prominently with Microsoft and NVIDIA to advance industrial automation and autonomous operations.
54 Use Cases in Industrial
| Company | Use Case |
|---|---|
| Caterpillar | Customer Support The Cat AI Assistant provides customers with voice-activated access to service information, fleet status, health diagnostics, and purchasing capabilities, improving customer experience through intelligent digital interaction. generative |
| Caterpillar | Autonomous Operation Caterpillar develops autonomous equipment capabilities, including remote control and AI assistant systems for construction machines, enhancing safety, operational efficiency, and reducing labor needs. agentic |
| Eaton | Modular Data Centers Eaton collaborates with partners like Flexnode to provide modular, scalable data center infrastructure optimized for AI computing, including critical power backup, racks, and cable management, significantly reducing deployment time for data centers catering to AI workloads. traditional |
| 3M | Product Innovation AI tools at 3M accelerate product development by analyzing data and simulating outcomes, allowing faster iteration and introduction of innovative materials and formulations. generative |
| Deere & Co. | Factory Optimization John Deere leverages AI combined with 5G connectivity and digital twins to improve manufacturing productivity through real-time quality control, predictive maintenance, and digital assistance for factory workers. traditional |
| 3M | Digital Assistant 3M launched 'Ask 3M', an AI-powered digital assistant that helps customers swiftly find solutions to complex design challenges using the company's extensive product portfolio. generative |
| Rockwell Automation | Edge AI Insights Introduced purpose-built edge-based generative AI models in collaboration with NVIDIA to deliver instant industrial insights and support offline decision-making in harsh environments. generative |
| Eaton | AI Infrastructure Architecture Eaton designs and implements next-generation power architectures such as 800 VDC infrastructure enabling AI factories and high-voltage direct current (HVDC) power systems for AI data centers, collaborating with NVIDIA to optimize power efficiency and capacity for AI workloads. traditional |
| Caterpillar | AI Infrastructure Support Investing in and scaling production of large engines and turbines that power AI data centers, Caterpillar capitalizes on the AI explosion driving demand for reliable electricity infrastructure. traditional |
| Rockwell Automation | Process Control Rockwell leverages AI-powered real-time data processing and machine learning to optimize utilities operations, reducing chemical consumption and energy use while maintaining quality. agentic |