Artificial intelligence and self-driving cars are often complementary topics in technology. Though AI is being implemented at rapid speed in a variety of sectors, the way it’s being used in the automotive industry is a hot topic.
How Artificial Intelligence Is Used in the Automotive Industry
With every car manufacturer and its parent company racing to develop artificial intelligence and self-driving technologies, there are also a slew of tech companies and startups with the same purpose.
Though many believe personal, autonomous vehicles are the future, there are multiple ways in which AI and machine learning are being implemented in how vehicles are built and how they operate on the road. AI in cars aims to improve vehicle safety, increase fuel efficiency and provide drivers with enhanced connectivity features.
Check out how these companies are using artificial intelligence in cars.
AI for Robotaxis
Robotaxis are a major trend in the self-driving vehicle space, promising safer and more efficient urban mobility. These vehicles use computer vision, a form of AI, to interpret camera and sensor data and offer ride-hailing services without a human driver.
May Mobility’s AI-driven system sets it apart from conventional autonomous vehicle approaches. Rather than relying on pattern-matching against training data, its system fuses a predictive world model with a real-time reasoning engine that simulates hundreds of possible futures every 200 milliseconds — predicting how drivers, pedestrians, and cyclists will interact and selecting the safest driving strategy accordingly. A remote assistance option remains available for edge cases the onboard system flags for human review. May Mobility has expanded beyond its early pilots, now operating across multiple U.S. markets and partnering with Uber, Lyft, Toyota, and others to scale its robotaxi business commercially.
Tesla manufactures electric vehicles equipped with machine learning and onboard cameras to recognize road objects and safely navigate during travel. The company’s driver-assistance systems, including Autopilot and Full Self-Driving (Supervised), enable its vehicles to automatically steer, accelerate, brake, lane change and park.
Waymo, formerly Google’s self-driving car project, is an autonomous driving technology company and leader of the autonomous driving industry. Its Waymo Driver technology enables autonomous planning and decision-making capabilities that extend beyond basic vehicle control, allowing the company to operate commercial robotaxi services across 10 U.S. metropolitan areas.
Zoox is an autonomous vehicle that builds robotaxis for driverless ride-hailing, with services across multiple U.S. cities, including Atlanta, Austin, Las Vegas, Miami and San Francisco. Its vehicles AI systems with sensor suites and radar that enable real-time decision-making, object detection and perception to prioritize passenger safety.
AI for Autonomous Vehicles
Many major auto manufacturers are working to create their own autonomous cars and driving features. Whether their technology is for use in public transportation, ride-sharing or personal needs, the following companies are at the forefront of autonomous vehicle technology.
General Motors has used AI in the past to optimize its manufacturing capabilities, and will soon use the technology to develop new driving technologies. The company will begin rolling out conversational AI — at first powered by Google’s Gemini model and later by a custom-built AI model. This new feature will learn driver preferences and communicate with drivers to spot maintenance issues or to route to a destination. General Motors also plans to release a driving assist feature that will allow drivers to take their eyes off the road in certain highways or conditions.
Magna International is a mobility tech company and auto supplier advancing AI across autonomous driving and manufacturing. The company’s thermal sensing systems use infrared imaging and AI algorithms to detect pedestrians, animals, and cyclists over 100 meters ahead, enabling enhanced emergency braking and nighttime safety — with over 1 million systems deployed across 50 vehicle lines. On the manufacturing side, Magna has partnered with Sanctuary AI to deploy general-purpose AI-powered robots in its facilities, complementing existing AI applications in predictive maintenance and decision-making
Motional, a joint venture between Hyundai Motor Group and Aptiv, develops autonomous driving technology using LiDAR, radar and camera sensors to prioritize safety. The company launched a commercial robotaxi service in Las Vegas in 2026 through a partnership with Uber, emphasizing end-to-end AI motion and Large Driving Model (LDM) technology.
Rivian is an electric vehicle manufacturer that develops the Autonomy+ platform, which enables hands-free driving on over 3 million miles of roads across the United States and Canada. The system uses HDR cameras and radar units to continuously learn from real-world driving data and improve performance, with features including Universal Hands-Free steering, Lane Change on Command and Co-steer assistance.
AI for Auto Manufacturing
With millions of cats produced globally each year, it’s no wonder manufacturers are seeking out machinery and ways to enhance production. Here are a few examples of how smart machinery and AI-powered systems are making automotive production lines more efficient.
ABB’s manufacturing robots use AI to inspect vehicle parts, paint and perform other automotive tasks. The company’s collaborative robots (cobots) also employ AI technology to sense the presence of people and objects, enabling safe human-robot collaboration on production lines.
BMW Group is a luxury automaker leveraging AI across its manufacturing ecosystem. The company’s iFACTORY strategy integrates AI to enhance production efficiency and quality control. Additionally, its AIQX platform monitors production lines in real-time, analyzing sensor and image data to detect errors instantly and reduce waste.
CCC Intelligent Solutions provides real-time data and insights to the automotive and insurance industries through AI-powered cloud technology and digital workflows. The company connects auto manufacturers, insurers and a network of more than 30,000 collision repair facilities, offering intelligence and data visibility for vehicle safety, durability and repair efficiency.
Rockwell Automation equips manufacturing robots with AI to support automotive production, including full vehicle assembly, paint application and precision part installation. Through its partnership with Nvidia, Rockwell Automation integrates applies its AI for Nvidia Omniverse (for factory-scale digital twins) and Nvidia Isaac (for autonomous mobile robots), enabling manufacturers to optimize quality control and reduce downtime.
AI for Driver Assistance
There are many different types of AI-powered advanced driver-assistance systems (ADAS) like automatic braking, driver drowsiness detection and lane departure warning. Some systems are even used by companies to re-train commercial drivers and avoid collisions. Here’s how a few companies are using artificial intelligence in cars for driver-assisted technologies to make the roads safer.
CarVi develops AI-powered driver assistance and fleet management software. Using a dashboard camera and computer vision, its platform monitors road conditions and driving behavior in real time, providing safety alerts and collecting driving data. Businesses can use the platform to monitor fleets, analyze driver performance and review footage from traffic incidents.
Motive builds hardware and software products that businesses can use to manage their vehicle fleets. Its AI-powered platform combines telematics, dashcams and edge AI processing to improve fleet safety and productivity, with Motive’s AI Dashcam Plus and AI Omnicam Plus running over 30 AI models on-device for real-time hazard detection and driver alerts.
Nauto is an AI-powered fleet safety platform that predicts and prevents collisions through real-time driver behavior monitoring and predictive risk analysis. Using video and facial recognition technology, Nauto’s AI models detect unsafe behaviors — including distraction, drowsiness and dangerous driving patterns — and alert drivers before an accident occurs.
AI for Autonomous Delivery
Takeout and grocery delivery services have been growing in popularity, with the online food delivery services industry projected to reach a market volume of more than $1.9 trillion by 2029. AI is bound to play a role in this growth, enabling self-driving vehicles to fulfill delivery orders. Here are three examples of autonomous delivery services making use of AI in cars.
DoorDash develops Dot, a commercial autonomous delivery robot that can navigate roads, sidewalks and bike paths using AI, cameras and LiDAR sensors to deliver orders. Capable of traveling up to 20 miles per hour, Dot represents DoorDash’s investment in autonomous vehicle technology for last-mile logistics.
Starship Technologies operates autonomous delivery robots that use machine learning, radars, cameras and sensors to deliver groceries, food and packages across over 300 global locations. With the ability to navigate at pedestrian speeds, cross streets, climb curbs and operate in various weather conditions, Starship’s fleet has completed over 10 million deliveries.
Other Uses of AI in the Auto Industry
Cox Enterprises is the parent company of Cox Automotive, which operates a portfolio of industry-leading brands focused on developing AI-powered solutions for automotive retail. For example, its Manheim marketplace uses M LOGIC, an AI decisioning suite that enables dealerships to set competitive prices, maximize profitability and connect buyers to ideal inventory.
HERE Technologies uses AI to power automotive-grade mapping and location intelligence for software-defined vehicles, serving major automotive manufacturers including BMW, Mercedes-Benz, Audi and Lotus. The company’s AI-powered portfolio combines live maps and advanced software tools that enable navigation, driver assistance and autonomous driving capabilities.
Toyota, in collaboration with Nippon Telegraph and Telephone (NTT), develops a Mobility AI Platform that captures real-world driving data to enhance driver-assistance systems and autonomous vehicle capabilities, including highway merging and accident prevention. Toyota’s Arene software platform, developed by subsidiary Woven, also integrates AI-driven features for personalized driving experiences and advanced safety systems.
Frequently Asked Questions
How is AI used in cars?
AI is used in cars in several ways, including powering sensors for autonomous vehicles and activating advanced driver-assistance systems (ADAS) to assist with things like braking and lane departure warnings. It is also being used in robots that assemble cars in factories.
What is the future of AI in vehicles?
Artificial intelligence will likely continue to support autonomous driving by gathering data from sensors, cameras, and 360-degree systems to help vehicles identify objects and anticipate dangers. It will also send real-time updates to connected cars, allowing them to interact more safely with other vehicles and objects on the road.
How do robotaxis and autonomous vehicles use AI?
Robotaxis and autonomous vehicles use AI — particularly a form called computer vision — to interpret data from cameras and sensors, allowing them to navigate traffic and road objects without a human driver. Companies like Waymo and Tesla are also developing more complex AI models for advanced planning and object recognition.
How does AI improve auto manufacturing?
AI is used to make auto manufacturing more efficient. For example, industrial robots can assemble and paint cars with precision. AI-powered systems can also use predictive analytics to assess performance history and detect potential issues on the production line, while other systems allow vehicles to share real-time data with employees to catch errors during assembly.
