Artificial intelligence accelerates digital transformation and enables various industries to change their business models. AI in the automotive industry is supposed to revolutionize the supply chains, improve the automotive manufacturing process, enhance quality control, simplify fleet management, and provide a new customer experience unlocking additional revenue streams for automotive companies. According to the latest studies, experts estimate that by 2030, 95-95% of new vehicles will be equipped with AI technology.
How the automotive industry works to get the most out of AI technologies
AI in the automotive industry isn’t a new trend. Automotive companies have been building AI teams for years. While many projects are run by their in-house AI teams, top automotive enterprises often collaborate with consulting and technology companies like Grape Up, experienced in delivering AI-powered solutions tailored for automotive.
Why do automotive companies decide to work with internal teams? Because software delivery experts provide broad expertise in building software products that tackle even the most demanding challenges. Know-how with implementing AI technologies, machine learning, and data science into production-ready solutions accelerates the process of developing and introducing innovative projects to end-users, and that’s a huge competitive advantage.
Artificial intelligence powering up the future of the automotive industry
Upcoming decades in the automotive sector will be dominated by the transition toward electric, self-driving cars. The most influential automotive companies focus their R&D projects on autonomous driving technology, connected cars, automotive value chain, driver assistance technology, parking assistance, shared mobility, risk assessment, and aftermarket services.
On the way to delivering fully autonomous vehicles, that leverage connected car technology, and provide a new customer experience, car manufacturers accelerate AI adoption. AI systems in modern vehicles use machine learning, data science, computer vision, natural language processing, neural networks, deep learning, and all helpful solutions that AI brings to the market.
By applying artificial intelligence technology to the software developed for modern vehicles, the automotive industry introduce advanced tools, such as predictive maintenance, driver monitoring, cruise control, and many more AI-powered systems that allows automotive manufacturers to stay competitive, increase efficiency, and prepare for the future vehicle sales.
Let’s see how artificial intelligence (AI) is changing the automotive industry by replacing traditional methods and tackling weak points.
AI in automotive manufacturing
Improving the production process and supply chain in the automotive industry
How artificial intelligence improves car manufacturing? Let’s start with an obvious fact – the vehicle manufacturing process is complicated. While an average passenger car consists of around 30K parts, chances for delays, shortages, and issues with the supply chain are huge. AI in the automotive industry can improve the entire supply chain management and provide auto manufacturers with actionable insights by verifying processes of part manufacturing, analyzing data from different stages of the automotive value chain, and monitoring global markets.
Also at the production level, AI technology helps automotive manufacturers improve work on production lines. In the automotive industry, employees can use AI-powered robots to complete more complicated tasks, do repetitive and boring jobs, and increase overall efficiency.
Enhancing the quality control of automotive solutions
Among artificial intelligence (AI) solutions that move work in the automotive industry forward are machine learning and data science. Every AI system used by the automotive sector in vehicle manufacturing collects car production data, learns details, and provides takeaways that help to improve quality. Vehicle manufacturers monitor their production processes with machine learning and computer vision technology to gain better results in finding weak points, enhance quality, and prevent failures and downtimes.
AI in automotive allows vehicle manufacturers to reduce costs of car production and avoid damages in the near future.
Providing new standards for vehicle customization
There is a growing market for personalized vehicles. With AI in post-production, vehicle sellers can use customer data and insights to deliver the dreamed car that for a client stands out from the crowd. The future of car selling is customization and presenting a personalized solution ahead of other vehicles. AI with access to good sources of data is a powerful tool that simplifies the vehicle seller’s job, improves customer experience (making a vehicle look unique in the driver’s eye), and accelerates the vehicle purchasing process.
Transportation supported by AI-based solutions
As in automotive manufacturing, also the future of transportation looks bright with AI technology. Artificial intelligence will enhance driving safety and provide driver assistance by analyzing driver behavior and vehicle data.
AI-powered assistance on the road
Data produced by vehicles and collected through access to communication technology allows AI to support drivers in the way they drive cars. Even before autonomous vehicles take over the market, driving behavior can gain a lot with all these suggestions from data and additional monitoring of the situation of the roads. In the end that will lead to reducing accidents and preventing collisions.
AI in the automotive industry will accelerate the entrance of autonomous cars but before the roads will be full of autonomous vehicles, AI-driven assistance is going to radically improve the driving experience and increase safety. When a driver gets exhausted, AI will support her/him. Once driving conditions become challenging, AI-powered solutions won’t get tired. Cars of the future, equipped with data science and AI technology will provide a new level of security and comfort.
AI algorithms enabling effective car maintenance
As AI technology is changing the automotive industry, the most established brands like Porsche, Mercedes-Benz, BMW, and Audi invest their resources into R&D projects that develop solutions for electric cars and autonomous vehicles. Along with improving driver experience and car manufacturing, Big Data and AI bring new quality to vehicle maintenance.
Data-driven predictive maintenance
AI enables car manufacturers to monitor sensors and vehicle data to detect upcoming issues in advance. AI-powered solutions allow for analyzing huge volumes of data and discovering potential failures and shortcomings long before they may occur. Cars equipped with predictive tools can be repaired in advance which helps to reduce costs and avoid problems during the journey.
By leveraging Over-The-Air updates, automotive companies can fix parts of their software (if the issue is related to the software) remotely which also reduces the time needed to visit the dealership.
Easy and tailored insurance
AI in automotive brings also new quality to car insurance. And the role of AI here is crucial both for insurers and for drivers. AI-powered tools allow for improving claim handling for insurance companies. Car owners can easily change or update their insurance program directly from their cockpit.
With amounts of data produced by vehicles and access to data covering driver behavior, insurance companies are able to provide more tailored and cost-effective programs, which is another benefit of equipping vehicle software with AI technologies.
How long will it take AI to revolutionize the automotive industry?
Experts from Grape Up forecast that it will take up to 10 years for AI to become omnipresent in automotive software and in vehicle manufacturing. Some of these solutions appear in modern cars, but the best is yet to come.
The automotive industry is preparing for AI adoption by running numerous R&D projects focused on AI-related technologies. Collaboration with experts in AI and automotive software development should accelerate the process and level up the quality of created software products.