"Data is the New Oil! How Analytics and AI are Changing the Game for the Auto-Aftermarket" took place at AAPEX on November 1.
The presenters were Tim Eisenmann, chief digital officer at American Tire Distributors/chief executive officer at Torqata, Andrew Brooks, SVP data & analytics at ATD, and Tilak Kasturi, CEO at Predii. Eisenmann pointed out that while artificial intelligence is not a new term, it has prevalence across many industries in modern times because leveraging that AI is easier. Simply put, more data is available these days than ever before.
So, what does this have to do with automotive? Katsuri said the shop of the future is one that considers "leveraging these insights in an effective manner." He said, with the power of data, shops may even be able to get to a point where they can anticipate maintenance needs before the customer even gets into the shop.
The presentation highlighted that in general, modern vehicles are more complex and data driven. There is an opportunity for AI and data to help navigate industry challenges, which, as shared from an ATD perspective, include supply chain SKU proliferation, fragmentation, lack of digitization, and supply chain disruptions. Eisenmann shared the example of mailers. Instead of blindly sending them out to customers and trying to track the return on investment, wouldn't it be easier to have a database dedicated to tracking promotions?
Enter: the conversation surrounding AI. As the title of the session alludes to, the presenters focused on the potential for data to be part of the industry lifeblood. According to the presentation, artificial intelligence, in a basic form, can make machines "smart." This gives the term a wide application.
"I cannot think of a machine that cannot be made smart," Eisenmann said.
He went on to say that embracing data and analytics will make the "winners" in this industry. Kasturi said AI should be looked at as a "co-pilot" to the industry, not a replacement. AI can become well-versed in automotive lingo and processes due to its ability to learn from historical data. It could learn and predict vehicle service needs.
But what does collecting this data look like in practice? To illustrate the answer, Brooks and Eisenmann pointed to ATD's recently announced Radius, a data-driven digital hub that helps to streamline inventory, service, solutions, and more. The software is a set of tools for tire dealers to use, and there is also a training element that can be utilized.
Predii has an offering as well: automotive AI. Katsuri gave a demo of the program during the presentation. It's an AI that is most reminiscent of something like ChatGPT, which Katsuri mentioned is a form of generative AI that took just two months to reach 100 million users. While Predii's offering may not be in the same usership category as that, the system is rather similar.
For example, when prompted with a service question, the automotive AI used historical context to answer as an automotive expert, make an assessment of the issue, and go into detail about the issue and what could cause it, as well as possible resolutions. When prompted with "Show me brake pads that fit on my customer's 2020 Ford F-150," the automotive AI turned into a parts representative, giving examples of brake pads and even linking to sources such as NAPA where the part can be purchased.
