Automakers are losing billions of dollars a year on costly warranty claims and vehicle recalls that could be saved thanks to artificial intelligence-powered quality control analysis.
This is the claim by Yoav Levy, co-founder and CEO of Upstream, a cloud-based data analyst platform currently serving 20 global automakers. Levy believes the century-plus reactive approach by automakers to fixing vehicle issues could soon be a thing of the past.
According to a report by Warranty Week, automakers worldwide are paying $51 billion in warranty claims and $140 billion in warranty reserves.
That said, while the rise of the software-defined vehicle (SDV) provides greater access to critical vehicle data, it also exposes more potential issues as new software is rolled out in over-the-air (OTA) upgrades.
However, Levy believes automakers can save between 5% and 20% of warranty and recall claims using the power of AI to predict quality issues before they are spotted by customers.
“With the movement towards the SDV we are seeing more and more quality issues arising with vehicle recalls and large warranty claims,” says Levy.
That’s because so many core functions of modern vehicles, especially the battery-electric vehicle, have been taken over by software instead of hardware.
“While BEVs are simpler cars, they have a more complex software stack because some of the hardware components have been replaced by software and, possibly, some of these OEMs have less experience in software development than hardware development,” Levy explains.
He also points to the pressure of speed being applied to legacy automakers by Chinese manufacturers who are pushing the industry to go faster in providing new features and services to consumers that can mean software systems are upgraded without adequate pre-launch testing.
Levy outlines the failings of the automakers’ current reactive approach to quality control where consumers spot a problem and have it fixed by a dealer who reports back to the manufacturer.
When a trend is spotted, the automaker has to issue a warning through the dealer network to look out for the issue with a specific component or vehicle model, possibly leading to a full recall when costs facing the automaker can escalate at an alarming rate.
“Naturally, this can take a very long time and with every day that passes, it costs the OEM an increasing amount of money because they are still building vehicles that have this quality issue during the investigation and the recall costs are then increasing every day.”
However, the modern SDV provides the answer with a mountain of data for the automaker to mine to identify potential future problems before they manifest themselves into customer complaints.
Couple this data with the power of AI to work through it at speed, and the automaker gets to be more out front in maintaining quality control.
“A connected car with AI capabilities can start to detect these indications or anomalies even before they start to see the claim,” Levy says.
With this AI technology, automakers can shorten the root-cause analysis in the investigation of potential issues, making greater use of the data platform and allowing AI to do the investigation faster.
Levy also points to the potential adverse effect on an automaker’s reputation through multiple recalls and reliability issues hurting the consumer’s ownership experience.
“It's billions of dollars on an annual basis per OEM,” says Levy. “So, it's a huge, huge issue especially now with where the automotive industry is going into cost reduction and competition with margins going down. Now, AI can help automakers be proactive rather than reactive to quality control issues.”
