Artificial intelligence is moving fast—and it’s already reshaping the automotive world.
According to Glide’s 2025 State of AI in Operations report, 73% of businesses are already using AI or have active plans to implement it this year. For automotive businesses like manufacturers and dealerships, this could mean major improvements in production, parts logistics, customer service, and more.
Is AI part of your operations yet? If not, keep reading to learn:
- Where AI is delivering the biggest wins for automotive businesses
- How leading companies are using automation to save time and money
- Other AI use cases that can change your operations in an instant
But first, let’s take a moment to define what AI in the automotive industry actually means.
What is AI in the automotive industry?
In the automotive industry, AI refers to smart technologies that help businesses automate operations, improve service, and make faster decisions. It powers everything from virtual agents that schedule service appointments to predictive tools that manage inventory and automobile parts logistics.
Today, AI is streamlining dealership operations, supporting customer service teams, optimizing manufacturing lines, and even helping finance departments forecast with greater accuracy. Rather than replacing workers, AI is giving automotive businesses faster, easier ways to get work done—and creating better experiences for customers at every step.
Benefits of AI for automotive businesses
In the automotive world, anything that saves time, reduces costs, and improves service is a win. Here are some of the biggest advantages you can tap into👇
Better manufacturing and quality control
Manufacturing cars comes with certain challenges. Even a small defect can lead to massive recalls—and major hits to brand reputation. In fact, vehicle recalls have been climbing for years. In 2024 alone, 27.7 million vehicles were affected by recalls. With more than one in four vehicles on U.S. roads now carrying at least one open recall, manufacturers face growing pressure to catch and correct issues faster than ever.
AI can help automakers spot issues earlier before they become expensive and public.
Computer vision systems powered by AI can inspect welds, paint jobs, and assembly components faster and more accurately than manual checks. Sensors and AI monitoring can detect anomalies in production lines long before a part fails in the field. And that’s just a few use cases that can help improve quality control and save you a lot of money down the road!
Optimized automotive supply chain management
Optimized automotive supply chain management is essential for keeping production moving by ensuring the right parts are available at the right time. Yet in recent years, supply chain delays have posed a major challenge for OEMs.
AI can forecast demand more accurately, track shipments in real-time, and recommend adjustments before problems snowball. Imagine an OEM predicting a parts shortage weeks ahead and shifting sourcing strategies early—that’s literally AI in action.
Elevated customer experiences
Today’s car buyers expect everything fast, personalized, and digital. AI makes it possible to offer that without overloading your staff.
In dealerships and service centers, automotive AI service tools can now handle many of the early touchpoints. For example, Capacity’s AI Voice Agents can pick up routine customer calls, like checking service hours or handling automotive scheduling for maintenance appointments, without tying up your workers.
On the customer communications side, Capacity’s AI SMS Automation lets businesses send real-time, personalized updates and appointment reminders directly to customers’ phones, boosting engagement and reducing no-shows.
Beyond quicker responses, AI can use customer data to offer more tailored recommendations and support, creating a smoother, more connected experience across every step of the customer journey.
Improved customer support efficiencies
If you’re a dealership or a car rental company, something you’re probably aware of is the sheer volume of customer questions that your support teams need to handle. Most of them are quite repetitive, which can be a huge time and resource suck. Just think—how many times does your staff have to answer questions about annual service appointment availability or warranty coverage terms? Yes, loads!
AI can step in and handle those repetitive tasks, so your team can spend more time helping customers with bigger, more complex needs.
Beyond just answering routine customer inquiries, AI can also improve internal knowledge sharing across your dealership network and service teams. With Capacity’s Enterprise Search Software, your staff can instantly surface the right information—whether it’s service manuals, parts databases, warranty documents, or CRM notes—without having to dig through multiple systems.
Instead of wasting time searching for answers, your team gets what they need in seconds. That leads to faster response times, fewer escalations, and major improvements in key support metrics like time to resolution, customer satisfaction scores, and average handle time.
Better business insights and decision-making
From service records and parts inventories to customer interactions and warranty claims, the automotive industry generates massive amounts of data. Turning that data into real-time, actionable insights is often easier said than done, especially across complex dealership, manufacturing, and supplier networks. But not with AI!
For instance, Capacity’s Analytics platform can give you instant visibility into customer interactions, service trends, and operational performance. You can monitor things like service ticket spikes, recall-related inquiries, and customer sentiment—all from one dashboard.
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Challenges of AI
As much as AI can be helpful in the automotive industry, it does come with certain risks you should be aware of—and be prepared to manage!
Black box problem
One of the biggest challenges with AI is the “black box” problem where AI models make decisions, but it’s not always clear how they got there.
If you’re using AI to help with things like warranty claims, customer support recommendations, or even predictive maintenance, you need to be sure your team can understand and audit how those decisions are made. Transparency matters, especially when customer safety or satisfaction is on the line.
Privacy concerns
Data privacy continues to be a huge concern with AI. In fact, according to Glide’s 2025 State of AI in Operations report, 51% of businesses in the planning stage cite data privacy and security as their biggest roadblock.
When you’re collecting customer data—whether through online service bookings, test drive forms, or AI chatbots—you should have strong privacy protections and choose vendors who take compliance seriously.
Bias and fairness
Even though AI is often praised for removing human bias, it’s not always perfect. If the data it learns from is biased, the results will be too. In one real-world case, a resume-screening tool favored applicants named Jared who had played lacrosse in high school.
In automotive businesses, this could show up if you’re using AI for things like staffing, financing offers, or customer targeting. Without careful oversight, AI might unintentionally favor certain groups over others or miss out on great candidates and customers. Regular audits, strong human review, and careful attention to how your AI models are trained are essential to make sure your tools are helping your business fairly and ethically.
Ethical guidelines
Lastly, although using AI undeniably provides a competitive edge, there’s a growing need for clearer ethical guidelines. As AI systems take on bigger roles in operations, customer interactions, and even hiring, companies must make sure they’re using these tools responsibly.
While many major players in the industry are beginning to lay out rules for how AI should be deployed—emphasizing fairness, safety, and transparency—there’s still a lot of work to be done. As a rule of thumb, before rolling out any AI tool, make sure you run it by your internal tech or implementation team.
4 Real-world applications of AI in the automotive industry
Despite the risks, businesses that approach AI with care are seeing major wins. Let’s explore some real-world examples of how AI is already transforming the automotive world.
1. Penske
Penske Automotive Group is one of the world’s leading automotive and commercial truck retailers, operating across the U.S. and internationally. In their rental division, they were facing a big challenge: too many last-minute cancellations and reservation no-shows, with not enough live agents to make outbound confirmation calls.
To solve it, Penske rolled out Capacity’s AI automotive solutions for reservation management. The results speak for themselves. Penske now confirms over 1,000 additional reservations every month, with AI handling 35% of all voice calls and 55% of all SMS conversations.
With Capacity, Penske was able to automate its outreach, freeing up its team to focus on more complex customer needs and ensuring fewer rental opportunities slipped through the cracks.
2. AAA
AAA, one of the largest roadside assistance providers in North America, needed a way to help stranded drivers faster—especially during major weather events when call volumes could spike overnight. Long hold times frustrated members, and their agents were overwhelmed.
To fix this, AAA partnered with Capacity to roll out an AI-powered Virtual Agent. The Virtual Agent greets members by name, identifies the reason for the call, verifies vehicle details, and even sends an SMS link to pinpoint the driver’s exact location—all without needing a live agent.
The impact has been huge: AAA has deflected over 30 million calls, cut costs per call by 66%, and boosted customer satisfaction to 4.5 out of 5. Now, even during winter storms, help is just a call—or a text—away.
3. AI Chatbots
Another way AI is transforming the automotive industry is through intelligent chatbots. Instead of making customers wait on hold or sift through websites, automotive AI chatbots deliver instant, helpful answers—anytime, anywhere.
For example, Hyundai uses its HeyHyundai chatbot to guide shoppers through vehicle research, test drive scheduling, and inventory searches. Drivers can ask questions like, “Which SUV has a Blind View Monitor?” or “Are there any Santa Fe Limited models in stock nearby?”— and get real-time responses.
Meanwhile, Europcar, a leading car rental company, uses an AI chatbot called Assistant Virtuel to guide customers through common tasks like booking a vehicle, modifying reservations, finding a rental location, or even retrieving invoices. If the chatbot can’t fully resolve an issue, it seamlessly redirects the customer to a live agent for further help.
AI chatbots allow to automate conversations that would otherwise require heavy staffing resources to be managed.
4. Predictive and advanced analytics
We’ve already seen how AI-powered chatbots are making customer support faster and more efficient. But AI is also helping automakers (and the businesses that support them) build better products behind the scenes.
Today, predictive and advanced analytics are playing a major role in the automotive industry. By tapping into real-time and historical data, automakers can spot quality issues earlier, reduce the risk of costly recalls, and deliver a smoother, more reliable ownership experience for drivers.
For example, Audi uses AI to detect tiny cracks in sheet metal during production, helping avoid costly defects. Similarly, Ford has rolled out an AI system across 20 of its plants to cut down on production mistakes. The technology checks hundreds of small assembly tasks, like making sure a rubber seal in a hybrid engine is fitted correctly.
5 Generative AI use cases for automotive companies
Now that we’ve covered how AI is already being used across the automotive industry, let’s look at a few more ways you can leverage the technology:
- Brainstorming new vehicle concepts and business models: You can use AI to help your teams quickly come up with new ideas for vehicles, features, and services by spotting patterns and suggesting fresh options you might not think of on your own. Instead of spending months in planning meetings, you can use AI to fast-track creative thinking and move faster from idea to execution.
- Virtual showrooms: Instead of relying solely on physical showrooms, you can use AI to build fully interactive, customizable digital experiences. Your customers can explore, configure, and “test drive” vehicles online, creating a seamless bridge between digital research and real-world purchasing.
- Generative design for car prototypes: With generative AI tools, your engineers can input specific goals like weight reduction, aerodynamics, or material constraints and instantly receive optimized design alternatives. This speeds up your R&D process, reduces prototyping costs, and often leads to more innovative solutions that outperform human-generated designs.
- Autonomous driving: AI helps cars “see” the road, understand what’s happening around them, and make quick decisions like when to stop or change lanes. It’s what makes self-driving cars possible. Getting this right not only keeps your drivers safer—it also gives you a big leg up over competitors who are still catching up.
Wrapping up
We’re living through one of the biggest shifts the automotive world has ever seen, and AI is right at the center of it. You don’t need to do everything at once. But you do need to start somewhere. Look for ways AI can take friction out of your customer experience, make your operations run smoother, or just free up your team, so they can focus on more complex tasks.
If you’re ready to take the next step, we can help you get there. Capacity’s AI automotive solutions are designed specifically for the automotive world, helping you boost sales, speed up service scheduling, and lower costs, all without adding extra headcount. From smarter chat and voice support to proactive outreach and instant lead capture, our platform keeps your customer experience fast, natural, and seamless. Book a free demo today to see the difference for yourself.
