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November 05, 2024

AI in the Automotive Industry: 10 Use Cases & Benefits

Author:




Edwin Lisowski

CSO & Co-Founder


Reading time:




12 minutes


The automotive industry is always quick to harness new technologies to introduce efficient, inventive, and safe cars into the market. A look at the annals of history shows how far the car industry has come; from steam-powered cars to gasoline-powered vehicles and now autonomous vehicles and electric-powered cars. Today, AI technology is at the forefront of success in the car industry.

AI is transforming the automotive industry in many ways, from enabling self-driving cars to transforming vehicle manufacturing and driving experience on the road. Consumers display an increasing fondness for autonomous driving systems. Thus, the AI in the automotive industry market is projected to grow tremendously in the coming years. According to a report by Global Market Insights Inc, the value of the automotive AI market will reach $12 billion by 2026. [1]

That being said, here are 10 ways how you can use AI in the automotive industry. At the end of the article, we will also say a few words about the future of the automotive industry.

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Use Cases of AI in the Automotive Industry

Autonomous vehicles

Self-driving cars are the new Holy Grail in the automotive industry. AI-powered technologies, including natural language processing, deep learning neural networks, and gesture control features, are great enablers of these autonomous vehicles. They act as the brains behind self-driving cars, with or without a human driver on board.

Tesla is an automotive company synonymous with electric vehicles. The company implements artificial intelligence technologies in its electric cars to turn them into autonomous vehicles and enhance the driving experience. For example, the autopilot feature typical of Tesla is a favorite for most buyers. In fact, it made Tesla the fastest-growing brand worldwide in 2021. [2] Drivers can switch to autopilot mode when they feel tired or dizzy and benefit from the advanced driver assistance system.

AI powers the autopilot neural network responsible for the Autopilot feature in Tesla cars. This neural network handles everything, from path-planning to controlling and identifying entities on the road to avoid crashes. [3]

Read more about AI in Automotive

Voice assistants

You’re probably familiar with voice assistants while using your smartphone. AI technology allows smartphones to understand human voice commands and respond accordingly. Voice assistants are also in use in the automotive industry.

Almost 125 million drivers in the US use voice control technology in vehicles today. [4] Drivers can issue voice commands to in-car voice assistants to perform different hands-free tasks, such as:

  • Placing and receiving hands-free calls
  • Receiving information from voice assistants about the nearest restaurant or gas station
  • Operating the radio streaming service
  • Controlling in-car temperatures, door locks, windshield wiper operation, and more
  • Finding available parking slots
  • Setting a destination and receiving directions while en route

car dashboard

Facial recognition systems

A facial recognition system uses AI technology to identify the individual’s facial attributes and determine whether to grant access or not. Car manufacturers like Porsche and Hyundai have adopted facial recognition systems to unlock their cars. [5] This feature allows car owners to restrict access to the car only to authorized persons. It is more secure than a traditional key fob.

Land Rover and Jaguar car manufacturers use facial recognition technology to control various in-car variables. For example, the tech can sense the driver’s facial expressions and automatically adjust the AC, lighting, and radio stations. [6]

It might be interesting for you: Using Artificial Intelligence (AI) for Image Recognition 

Research and development of new solutions

AI’s ability to think like humans and imitate their actions makes it a key component in the research and development of new solutions in the automotive industry.

General Motors, for example, uses AI-based algorithms and cloud computing to explore several permutations of a part design to make their vehicles lighter and more efficient.

Recently, they created a seat bracket design that is 40% lighter and 20% stronger compared to the original part. It also merges 8 different parts into a single 3D-printed component. [7] This way, artificial intelligence is being used to bring inventive solutions to car manufacturing.

Research and development of new solutions

Quality control

Artificial intelligence has the inherent ability to analyze massive datasets and draw valuable insights. AI-based hardware, for example, can visually examine and provide comprehensive quality control for different products. These include machined components, texture metal surfaces, painted car bodies, and more. Thus, car makers can prevent defective car parts from leaving the factories.

For example, Audi employs computer vision to identify small fissures in the car’s sheet metal. So, even at the manufacturing stage, it mitigates the risk of faulty parts leaving the production facility.

Assembly automation

The automotive industry always seeks to achieve efficiency on the production line, especially with workers susceptible to fatigue or safety risks.

Industrial robots first came into the picture in the 1960s. They can perform tasks like windshield installation, screw driving, and wheel mounting. Artificial intelligence technologies have brought a new generation of robotic solutions to work side by side with humans at car assembly plants. These are called collaborative bots (co-bots).

Assembly automation

AI-driven co-bots are smaller than typical industrial robots. They use sensors to prevent collisions and injuries at the worksite. And they can complete myriad tasks, from moving heavy components and assembly to conducting tests in the factory. Automating repetitive assembly tasks eradicates human errors.

Driving behavior analysis

Installing computer vision-powered cameras in the car can analyze the driver’s behavior. For example, Tesla cars monitor the driver’s eyes to check for fatigue and prevent them from dozing off during travel.

These AI-powered cameras can detect unusual activities, including:

  • Driver fatigue
  • Driver distraction
  • Cell phone usage
  • Low blinking rate
  • Falling asleep

The system then alerts the distracted driver to stop the car on the side of the road, which helps avoid accidents.

Predictive maintenance

Modern cars will alert you when something goes wrong – oil leak, brake pads, engine light. AI adds even more possibilities through predictive maintenance.

It leverages tons of data gathered from sensors and service records to analyze and detect car problems before the “check engine” light turns on. This forecast helps eliminate safety hazards and avoid expensive repairs.

Predictive car maintenance

Streamline auto supply chains

A typical passenger car comprises thousands of parts that originate from different manufacturers across the globe. Thus, the automotive industry has highly complex supply chains that could suffer significant financial losses in the event of potential breakdowns or delays.

AI provides three essential advantages in alleviating core issues that lead to supply chain failures: speed, transparency, and predictive ability. Car makers now rely on AI for greater visibility and real-time tracking of the shipping process of car components. AI also speeds up things by automating requests for components, labor, machinery, and repairs.

Moreover, the automotive industry can rely on AI-based tools to predict manufacturing downtime. This helps avoid unplanned and costly disruptions in the supply chain.

Personalized marketing and sales

Today, many car dealerships leverage AI to offer personalized marketing to customers. AI gathers customer data from all touchpoints, including the search engine, website, mobile apps, social media, and more. It then analyzes the data and narrows it down to the specific car features, make, and model that a specific customer would want based on their search intent.

The sales representative can then recommend a few car options to the potential customer that matches the search criteria they were looking for. Thus, each car recommendation is intentional, relevant, and personalized.

Impact of AI on the automotive industry: Manufacturing processes

Artificial Intelligence (AI) is not only transforming the automotive industry—introducing innovations like autonomous driving and advanced driver assistance systems—but it’s also revolutionizing the processes used to manufacture these vehicles. From enhancing production efficiency to improving quality control and safety, AI technology is redefining how cars are made.

The integration of AI into manufacturing processes is enabling automotive companies to achieve higher levels of precision, speed, and flexibility, reshaping the industry in profound ways.

Here’s a closer look at the critical areas where AI technology is making an impact in automotive manufacturing:

Quality Control Automation

Advanced AI-driven quality control systems are reshaping vehicle inspection processes. Using computer vision, AI systems can identify defects with remarkable accuracy, detecting even the smallest flaws that human inspectors might overlook. This automation accelerates the inspection phase and ensures that only top-quality vehicles reach the market, reducing the chances of recalls and enhancing customer trust.

Collaborative Robotics

Collaborative robots, or “cobots,” powered by AI are now working alongside human workers on assembly lines. These robots are designed to learn from human actions, adapt to changing environments, and improve efficiency and safety. By enhancing human-robot collaboration, cobots speed up production times, reduce costs, and lower the risk of workplace injuries, making manufacturing safer and more efficient.

Design Innovation

AI is also making waves in vehicle design, allowing automotive companies to leverage simulations and virtual modeling. Engineers can now test different configurations without needing physical prototypes, speeding up the design process and fostering innovation. This approach not only shortens development timelines but also enables the creation of vehicles with improved performance and safety features.

Data-Driven Insights

Automotive companies generate vast amounts of data throughout the production process. AI can analyze this data to uncover actionable insights, helping manufacturers make better decisions on production strategies, resource allocation, and process improvements. These insights lead to greater productivity, allowing manufacturers to meet production goals more effectively.

Benefits of AI in the automotive industry

From enhancing safety features to optimizing manufacturing processes, AI is driving significant advancements that improve operational efficiency and create new business opportunities. Below are some key benefits of AI in the automotive industry, along with supporting statistics and their sources.

Increased operational efficiency

AI optimizes manufacturing processes through predictive maintenance, which can reduce equipment failure by up to 20% and decrease total annual maintenance costs by as much as 10% (Source: Trade & Industry Development).

Improved safety

AI significantly enhances vehicle safety through advanced driver-assistance systems (ADAS). Features such as automatic emergency braking and lane-keeping assist help prevent accidents, with studies indicating that these systems can reduce crash rates by up to 30% (Source: Trade & Industry Development).

New business models: autonomous vehicles

AI is essential for developing autonomous vehicles, which are expected to constitute 10-15% of new car sales by 2030 (Source: Trade & Industry Development). This shift not only transforms transportation but also creates new business models and revenue streams for the automotive industry.

Supply chain management

AI and machine learninganalyzes data to predict demand for various vehicle models, optimizing production schedules and inventory management. This capability reduces costs associated with overproduction and ensures timely delivery of parts, enhancing overall supply chain efficiency (Source: Fullpath).

Predictive maintenance

AI-powered predictive maintenance is a game-changer in automotive manufacturing. Machine learning algorithms analyze real-time data from equipment to predict potential failures before they happen. This proactive approach reduces costly unplanned downtime and ensures a steady production flow. By enhancing machinery reliability, automotive companies can minimize disruptions and optimize the lifespan of critical equipment.

Sustainability initiatives

AI supports the automotive industry’s transition to eco-friendly practices by optimizing energy consumption in electric vehicles and enhancing production processes to reduce waste (Source: Cloud4C).

Future of the automotive industry

The automotive industry is on the brink of a transformative era, driven by advancements in technology and changing consumer preferences. As electric vehicles (EVs) gain traction, the market for EVs is expected to grow significantly, with projections indicating that global EV sales will reach 30% of total vehicle sales by 2030.

This shift is not only about electrification; it encompasses the rise of autonomous vehicles and the integration of artificial intelligence (AI), machine learning included, into various automotive processes. By 2033, the AI market in the automotive industry is projected to reach approximately $35.71 billion, highlighting the critical role AI will play in shaping the future of mobility (DataForest).

Do you want to implement AI in your automotive company?

Take a look at our AI consulting services.

AI in the Automotive Industry – FAQ

What is the impact of AI on the automotive industry?

AI is transforming the automotive industry by enabling advancements in autonomous driving, enhancing manufacturing processes, and revolutionizing the in-car experience. Through AI, car manufacturers can improve operational efficiency, safety, and the overall quality of vehicles, while creating new business models centered around technology-driven solutions.

How does AI improve vehicle safety?

AI enhances safety both on the production line and in vehicles themselves. In manufacturing, AI-driven cobots reduce workplace injuries, while AI quality control systems ensure vehicles meet high safety standards. On the road, AI supports advanced driver-assistance systems (ADAS) such as emergency braking, lane-keeping, and driver-monitoring technologies to prevent accidents and enhance overall driving safety.

Can AI enhance personalized driving experience in cars?

Yes, AI enhances the driving experience, for example, by powering voice assistants and facial recognition systems within vehicles. These technologies allow drivers to issue voice commands for hands-free controls or access secure systems through facial recognition. Additionally, AI can customize in-car features—such as temperature, lighting, and seat positioning—based on user preferences.

What are the benefits of AI for automotive supply chain management?

AI improves automotive supply chain management by providing real-time tracking, predictive analytics, and automated demand planning. AI-driven tools streamline logistics, prevent supply chain disruptions, and reduce costs. By predicting demand more accurately, car manufacturers can ensure that components are available when needed, supporting efficient production.

This article is an updated version of the publication from July 5, 2022.



Category:


Artificial Intelligence