Artificial Intelligence in Automotive Companies
We analyzed the enterprise AI use cases of 10 automotive companies to understand trends, impact, and insights.
Automotive companies' adoption of AI
Overview
General Motors has steadily increased its AI integration across manufacturing, supply chain management, autonomous vehicle development, and customer-facing applications between 2021 and early 2026, highlighted by key hires such as Chief AI Officer Barak Turovsky and partnerships with technology leaders like Nvidia and Google.
Ford has steadily increased its AI integration from basic interactive installations and quality control automation in 2018-2019 to advanced autonomous driving development by early 2020s, including forming Latitude AI and trialing AI driving tech on assembly lines.
Tesla has steadily increased its AI adoption across its vehicle autonomy, manufacturing, and robotics platforms from 2021 through early 2026, with key products including Autopilot, Full Self-Driving (FSD), the Cybercab robotaxi, and Optimus humanoid robots.
Stellantis has been steadily increasing its investment and integration of AI technologies from 2021 through early 2026, aiming for a €20 billion annual revenue by 2030 fueled by connected and AI-driven technologies.
Toyota has progressively integrated AI from foundational research established in 2015 to advanced generative AI techniques in vehicle design by 2023, and now employs agentic AI and unified data platforms by 2026.
Honda has steadily increased AI adoption from initial exploratory patent portfolio management (2019-2020) to deploying advanced AI systems in vehicles and manufacturing by 2025-2026, including AI-powered autonomous driving, driver assistance, and vehicle personalization technologies.
BMW has progressively expanded AI adoption from quality control in manufacturing to advanced generative AI and autonomous robotics by 2026, significantly enhancing production efficiency and product quality.
Mercedes-Benz has steadily integrated AI into both manufacturing and user experience, progressing from digital production systems in 2023 using NVIDIA Omniverse and MO360 to advanced humanoid robotics and AI-enhanced assembly lines by early 2025.
Hyundai Motor Group has progressively expanded its AI adoption from improving vehicle transmission performance in 2020 to developing in-car AI systems, AI-powered manufacturing, and smart city solutions by 2026.
Rivian has progressively integrated AI across vehicle design, manufacturing, driver-assist/autonomy features, and user experience. This includes IP development with 5 AI patents in early 2024, autonomous driving ambitions positioning Rivian to compete with Tesla, and in-house AI models and chips unveiled by late 2025.
63 Use Cases in Automotive
| Company | Use Case |
|---|---|
| Honda | Battery Development Honda utilizes AI-driven material exploration and modeling to accelerate R&D of advanced ternary and quaternary materials for next-generation EV batteries. traditional |
| Hyundai | Robotics Automation Hyundai invests heavily in AI robotics, deploying on-device AI chips for autonomous robots and developing a $6.3 billion complex for AI data centers, robot manufacturing, and hydrogen production to lead human-centered robotics innovation. agentic |
| Mercedes-Benz | Driver Assistance The NVIDIA DRIVE AV software integrated into Mercedes-Benz vehicles delivers enhanced Level 2 driver assistance capabilities, improving safety and driver comfort with point-to-point AI-defined navigation. agentic |
| BMW | Robotic Automation Deployment of humanoid robots in production lines enhances flexibility and competitiveness, integrating AI and digitalization under BMW iFACTORY initiatives. agentic |
| Stellantis | Supply Chain Stellantis employs AI-enabled multimodal logistics and collaborative programs to increase supply chain resilience and efficiency, combining human expertise with advanced AI-driven decision support systems. traditional |
| Honda | Road Maintenance Honda employs AI and onboard vehicle sensors to detect potholes and road hazards in real time, enabling proactive roadway maintenance and safer driving conditions. traditional |
| Toyota | Data Integration Toyota adopted the Databricks Data Intelligence Platform to unify and democratize data across the company, enabling widespread AI readiness and integrated operations. traditional |
| Ford | Customer Assistance Ford introduced an AI assistant chatbot on mobile app and integrated AI assistants in vehicles to provide customers with vehicle-specific advice, improving user experience and vehicle interaction. generative |
| Mercedes-Benz | Process Optimization By leveraging platforms like Celonis Process Intelligence combined with AI, Mercedes-Benz has improved on-time delivery and enhanced decision-making across its production networks, driving operational efficiency. traditional |
| Rivian | Autonomous Driving Rivian develops machine learning models and sensor-rich platforms enabling driver-assist and fully autonomous driving capabilities, supported by a proprietary in-house AI autonomy platform and custom AI silicon chips. agentic |