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
John Deere has shown a clear and accelerating adoption of AI technologies from 2018 through to 2025, evolving from basic machine learning applications like 'See and Spray' for weed detection to advanced autonomous farming machinery and predictive analytics integrating edge computing and satellite connectivity.
General Electric has steadily increased its adoption and deployment of AI technologies from early digital transformation efforts in 2016-2017, evolving into broad industrial AI applications by 2025 including predictive maintenance, generative AI, and emissions management.
3M has progressively integrated AI across its operations from 2018 through 2025, evolving from predictive healthcare and supply chain analytics to advanced AI-powered tools in manufacturing, healthcare, and customer innovation.
Honeywell has demonstrated a strong, accelerating adoption of AI technologies from Q4 2023 through 2025, expanding from aerospace digital assistants for single-pilot operations to broad enterprise-wide AI initiatives impacting 95,000 employees and generating over $100 million in value.
Since 2018, Caterpillar has progressively integrated AI and machine learning into its operations, starting with data management integration with OSIsoft, then using machine learning to enhance performance and reduce costs by 2021, advancing to autonomous tech and generative AI capabilities development by 2024-2025.
Emerson Electric has progressively integrated AI technologies across its industrial automation, power, and water management solutions, advancing from AI-enabled software automating 70% of system configuration in Q3 2023 to launching GenAI-enabled platforms by mid-2025. Key products include the Ovation 4.0 Automation Platform with AI-powered Virtual Advisors enhancing real-time decision-making and operational efficiency.
Parker-Hannifin has progressively integrated AI technologies from 2022 through 2025, initially partnering with AI firms like Camgian to co-develop AI-enabled digital enterprise solutions and advanced vehicle self-diagnosis capabilities.
Illinois Tool Works (ITW) has progressively integrated AI, particularly in predictive maintenance and manufacturing innovation, enhancing operational efficiency by 2025 while maintaining a $16 billion revenue scale.
Eaton has significantly expanded its role as a critical infrastructure provider for AI data centers and edge computing from 2023 through 2025, with innovations in power management, modular data centers, and AI load spike detection.
Rockwell Automation has increasingly integrated AI and generative AI technologies since 2019, collaborating notably with Microsoft and Nvidia to enhance industrial automation, predictive maintenance, and autonomous operations.
52 Use Cases in Industrial
| Company | Use Case |
|---|---|
| 3M | Customer Innovation 3M launched an AI-powered digital assistant, Ask 3M, which helps customers quickly find solutions across its vast product portfolio, enhancing customer experience and innovation speed. generative |
| General Electric | Imaging Enhancement GE HealthCare employs AI to improve diagnostic imaging technologies such as MRI and CT scans, delivering superior image quality, reduced scan times, and enhanced diagnostic accuracy. traditional |
| Honeywell | Workforce Enhancement Honeywell integrates AI-driven speech recognition and generative AI copilots into frontline and retail workforce tools to improve task accuracy, speed, and employee performance. generative |
| 3M | Data Center Efficiency 3M develops advanced materials like optical fiber interconnects and sensor-enabled cables designed to reduce energy consumption, improve reliability, and support high-speed connectivity in data centers critical for AI workloads. traditional |
| Eaton | Power Management Eaton uses AI and edge-based analytics to detect and mitigate power load spikes and subsynchronous oscillations in data centers, preventing overheating, equipment damage, and costly outages, thereby enhancing infrastructure resilience. traditional |
| Rockwell Automation | Resource Management AI-driven solutions optimize water treatment and power generation regulation, improving efficiency, sustainability, and reducing chemical and energy usage. traditional |
| Caterpillar | Capacity Expansion To meet the surging power demands of AI data centers, Caterpillar is expanding its large-engine manufacturing capacity, underscoring the role of AI-driven infrastructure in its business growth. traditional |
| Emerson Electric | Data-Driven Decision-Making Emerson’s AI-enabled industrial data fabric platforms, in partnership with companies like TotalEnergies, aggregate and analyze real-time industrial data to enhance operational decisions and energy efficiency. traditional |
| Honeywell | Predictive Maintenance The company’s AI platforms analyze real-time data from building systems to predict maintenance needs, optimize energy usage, and prolong asset life. traditional |
| Emerson Electric | Predictive Maintenance AI models integrated into Emerson’s Guardian Virtual Advisor analyze historical and real-time data to forecast equipment failures and schedule proactive maintenance, minimizing unplanned outages and extending asset lifespan. traditional |