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Welcome to The Breakdown, an analysis of auto retail’s top trends, moves, and insight in under 5 minutes.
The car biz has typically been defined by thin margins, turbulent inventory dynamics, and fierce competition from both traditional and digital-first players.
But now, retailers are operating in an environment where AI is directly handling data-heavy processes consistently and intelligently, allowing teams to go after more high revenue-generating tasks.
And in my opinion, these dealers have some of the best AI deployment strategies in the game today..
Van Horn Auto uses AI as its front‑line BDC rep.
This week, I caught up with Van Horn’s innovation and technology specialist, Tina Tasche, who told me that AI now takes the first swing on basically every inbound lead/inquiry and only kicks the more complex, higher‑intent cases to humans.
And it’s working:
Lead response time on chat/text is now roughly 30 seconds, day or night.
In September, only ~19% of shoppers engaged with AI messages. Today, that number is 41%.
And over the same time period, the percentage of customers who engaged back-and-forth with the AI grew from 10% to 23%.
The secret sauce is treating the AI tool like a “living script.”
For example, every six weeks, Tasche sits down with Van Horn’s pre-owned leadership team and reviews what’s working and what’s not when it comes to inventory acquisition messaging.
Tina Tasche
Van Horn Auto Group
They test shorter, more direct openings, tighten follow‑up cadences, and kill anything that doesn’t move one simple metric:
Did more customers keep talking to us?
The result: Reps log in to queues full of conversations that already have context, replies, and often a proposed appointment time. Their job then shifts from “try to wake up every cold lead” to “prioritize the warmest threads and close.”
And because AI is handling the repetitive first touches and nudges, Tasche can pull employees for coaching and training without torching response times.
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Longo Toyota is deploying AI to unclog service department traffic jams.
Longo Toyota service director Paul LeBlanc oversees about 370 repair orders a day (around 9,000 repair orders a month) with 88 main‑shop techs and more than 200 total service team members.
However:
Roughly 1 in 4 calls into a dealership is mismanaged, per Numa.
And in service, 82% of customers who leave a store say they did it because of poor communication.
“I've always said if your guest is calling you, then you failed. They should never have to call you. You should be calling them before they need an update from you,” said LeBlanc.
Paul LeBlanc
Longo Toyota
So, instead of throwing more bodies at the phone tree, Longo is using AI to take the weight of all those “any update on my car?” calls off the human team.
What that looks like in practice:
AI pulls live RO status from the system and pushes out clean, proactive updates so customers don’t have to guess.
The routine back‑and‑forth (appointment confirmations, simple timing questions, transportation logistics) gets handled automatically.
And advisors + service BDC staff spend more time on getting real approvals.
At Longo’s scale, the difference between controlled chaos and total gridlock is about making sure the right people are handling the right calls.
Rohrman Auto and Fox Motors are proving that AI is useless without clean data.
The golden rule: If your data is garbage, your AI deployment likely will be too.
Rohrman Auto Group dug into its own records and found that only 48% of customer profiles were actually accurate on the basics, like contact info and current vehicle ownership.
That means more than half of their “personalized” outreach was aimed at the wrong person, the wrong car, or both, explained sales and digital retailing director Jeremy Nowling.
Jeremy Nowling
Rohrman Auto Group
So, they started by fixing the foundation.
Rohrman pushed a fully enriched dataset into Snowflake, then treated it as the real source of truth for the group. Leadership now calls it “what a DMS should be” because operators can finally slice performance by rooftop, brand, region, or customer segment without exporting a dozen spreadsheets and praying they line up.
And this reminded me of Yuriy Demidko, senior VP and chief information officer at Fox Motors, who built an AI tool that pulls in reviews from every major channel into one place and then uses AI to mine for customer sentiment patterns across the entire group like:
Are customers consistently confused about what’s covered under warranty?
Is one store getting hammered on service wait times while others aren’t?
Is there a specific advisor, department, or process that keeps coming up?
Once those patterns show up in the data, Fox can do two things at once; fix the underlying issue and re‑engage the customers who were burned.
The big takeaway here is that no amount of fancy AI or extra ad spend can save a dealership if the upstream data is garbage.
Bottom line: Results will always vary by store size, market, and how well AI rollouts are managed. But aggregated industry reporting shows consistent revenue uplift, meaningful reductions in operational overhead, and improved customer satisfaction scores.
Yet, that success is rarely plug-and-play. The highest ROIs will go to the organizations that prioritize clean data integration, phased rollouts focused on high-pain areas, and cultural alignment to ensure staff embrace the tech rather than resist it.
Missed Wednesday’s episode of Daily Dealer Live?
Presented by:
Horner on Used Strategy, Riley on Loyalty
Featured guests:
Doug Horner, GSM of Mercedes-Benz of North Olmsted
Jameson Riley, General Manager of Riley Volvo
