Artificial intelligence isn’t just hype anymore; it’s showing up in service lanes, call centers, and marketing campaigns across the industry. But while the potential is big, the application often feels… messy.
That’s because many tools promise to fix retention, boost efficiency, or predict defection, but end up creating more dashboards, more complexity, and more confusion.
Todd Smith, CEO and co-founder of QoreAI, wants to change that.
In a recent episode of the Retention Roadmap podcast, Todd unpacked how dealerships can use AI to cut through the noise, connect with customers more personally, and make smarter decisions faster. From data hygiene to behavior-based messaging, his advice is practical, scalable, and grounded in real dealership operations.
The key takeaway? You don’t need to start big, but you do need to start smart.
Step One: Clean Up Your Data Before You Touch AI
Before you even think about plugging AI into your dealership operations, you need to get your data house in order. That’s the first (and arguably most important) step Todd recommends.
Dealerships are sitting on mountains of data across platforms like the DMS, CRM, service scheduler, website, and more. But that data is often fragmented, duplicated, or just plain wrong. AI can’t make smart decisions if it’s working with bad information.
Todd breaks the process into three steps:
- Organize: Pull data from all systems into one consistent format. This creates a unified “data schema” AI tools can actually use.
- Hygienize: Clean it up. Remove duplicates (like three versions of the same customer because different family members brought in the car).
- Enhance: Add useful third-party data like household type, income range, and behavior patterns to give context beyond transactions.
Without this foundation, AI becomes another expensive tool that doesn’t deliver.
From “Set It and Forget It” to “One Size Fits One”
Dealerships have traditionally relied on automated marketing that follows a rigid timeline with 30-day, 60-day, and 90-day reminders. But that approach can actually train customers to ignore you.
AI gives you a better option: Send the right message at the right time, based on each customer’s actual behavior.
Let’s say a customer usually services their vehicle every 6 months, but now it’s been 8. That’s a defection risk, and a perfect time for a personalized outreach. AI can identify those patterns automatically and trigger a message before the customer disappears.
This is where the real power of AI starts to show up:
- Fewer irrelevant messages → Less fatigue, fewer opt-outs
- Better timing → More responses, more booked appointments
- Personalization that feels human → Higher trust and loyalty
As Todd puts it, “We’re not trying to blast everyone. We’re trying to understand them.”
Spot Risk (and Act on It) Before It’s Too Late
Not all customer losses happen loudly. Most of the time, they just stop showing up, and you don’t notice until it’s too late.
That’s why Todd sees predictive defection as one of AI’s biggest opportunities in fixed ops.
By analyzing service cadence, RO status, review behavior, and even driving patterns, AI can flag when something feels “off.” Maybe a customer who usually comes in every six months is overdue. Maybe they had a long-open repair order and never returned. Maybe they left a one-star review that no one followed up on.
With AI, these signals trigger alerts, prioritize outreach, and even recommend the right team member to respond (like a service manager instead of an advisor).
One standout example?
Todd’s team used AI to identify customers who had recently declined tires or brakes, then proactively reached out before a winter storm. Not only did it feel thoughtful to customers, but it also filled service bays without a generic blast.
The bottom line: AI gives your team the ability to intervene early and make retention feel personal again.
Start Small, Win Fast
When it comes to implementing AI, many dealership leaders assume it’s an all-or-nothing move. But Todd advises the opposite: aim small, win fast.
The best place to start? Pick one repetitive, time-consuming task and see how AI can lighten the load. Think payroll calculations, declined RO follow-ups, or summarizing reports.
Todd shared the example of the “Emily Project,” named after an employee who used to spend days calculating sales and service advisor pay across a large dealer group. With AI, the same process now takes 15 seconds, freeing her up to focus on more valuable, strategic work.
The lesson? You don’t need to reinvent your service department overnight. Just identify one workflow where AI could save time, reduce manual effort, or improve accuracy.
And when those early wins start stacking up? That’s when buy-in grows, confidence builds, and you’re ready to scale.
The Dealers Who Win with AI All Have This in Common
The biggest difference between dealerships who are succeeding with AI and those who are still spinning their wheels? Mindset.
According to Todd, the best-performing stores aren’t the ones with the biggest budgets or flashiest tech—they’re the ones willing to experiment, learn, and evolve.
They treat AI like a new team member: train it, test it, and give it time to grow into the role.
That means letting go of the idea that AI is a plug-and-play solution. It’s not. It’s a process. One that pays off for dealerships that start early and stay committed.
Just like the internet disrupted everything in the 2000s, AI is doing the same now, but faster. Waiting for it to be “proven” could leave you trailing competitors who are already turning their service data into retention gold.
Todd puts it simply: “It’s better to be a warrior in a garden than a gardener in a war.”
The earlier you start training your systems and your team, the better positioned you’ll be when retention truly goes predictive.
Want to hear the entire conversation? Listen to the full episode here.
Need help making retention feel automatic?
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