Every major dealership technology shift comes with the same advice: someone else will figure it out first, then you'll adopt what works. Mia's Scott Traylor and Thuy Adomitis are telling dealers plainly that this time, that playbook is a losing bet.
Traylor and Adomitis joined the show to make the case that AI adoption in dealerships isn't following the same timeline as past shifts, and that the dealers waiting for a settled "right way" to do this may not get the runway they're expecting.
The Comparison Everyone Reaches For Is the Wrong One
Traylor's framing draws a direct line back to dealership websites replacing faxed leads, newspaper ads, and paper inventory grids. That transition took years to fully play out. His read on AI: the same shift, except compressed.
You don't have that long. This is hitting different.
The Hallucination Fear Isn't Playing Out the Way the Industry Expected
One of the loudest objections to dealership AI adoption is the fear of hallucinations, an AI system confidently giving a customer wrong information. Adomitis's read from Mia's actual early users pushes back on how big that risk has been in practice.
We haven't seen the widespread hallucination problems some in the industry fear, though edge cases will always exist and need to be resolved.
That's not a claim that the risk is zero. It's a claim that the risk has been smaller and more manageable in real dealership use than the industry's loudest fears suggested.
Why Getting In Early Matters More Than It Sounds Like It Should
The advantage of early adoption isn't just experience. It's data.
The cool part of AI is you only have to train it one time.
Every month a dealership waits to start is a month of training data it isn't accumulating, while competitors already in the game are teaching their systems the specific patterns of their own customers, their own inventory, their own market.
The Stores Actually Winning With This Treat AI Like a New Hire, Not a New Tool
Traylor's pattern-matching across Mia's best-performing dealerships points to one consistent trait: leadership buy-in from the top, not a mandate pushed down from a single department.
Position the technology as an ultimate employee, one that helps cover customer traffic humans are leaving untouched, while freeing support staff for other work.
That reframing matters. An "ultimate employee" doesn't replace the team, it covers the gaps the existing team was already unable to reach, freeing real staff to focus where a human actually adds more value than a bot ever could.
🎙️ Listen to today's Automotive State of the Union episode for the complete discussion.
The dealerships treating AI like software to evaluate are moving at software speed. The ones treating it like an employee to train are already ahead.
Every past technology shift in this industry rewarded patience, wait for the kinks to get worked out, then adopt the mature version. Traylor and Adomitis are making a specific, falsifiable claim that this cycle doesn't behave the same way. Whether that claim holds up is something every dealer still on the sidelines will find out either way, just not necessarily on their own timeline.
