Despite economic downturns, new competitors, changing customer expectations, inventory shortages, new technology, and predictions that the traditional dealership model was on its way out, the average franchise dealership in America has remained profitable for the past 50 years.
Through it all, dealers have adapted.
So, what do the next 50 years look like?
His answer: Artificial intelligence could give dealerships an opportunity not just to protect profitability, but to raise the ceiling.
Fifty Years of Resilience
Using data from NADA, Greenfield looked at average dealership net profit before tax over the past 50 years.
One finding immediately stood out: Not once during that period did the average U.S. franchise dealership lose money.
Before the COVID-19 pandemic, average net profit before tax generally stayed within a range of roughly 1.5 to 2.5 percent. Pandemic-era supply constraints pushed profitability well above historical levels, and while it has declined since, the average dealership still delivered 3.3 percent net profit before tax in 2025.
History suggests that profitability could continue moving toward its long-term range.
But Greenfield sees another possibility.
AI could help dealerships create a massive change in productivity, allowing them to operate at persistently higher levels of profitability.
The question is how.
Not All Revenue Is Created Equal
The answer starts with understanding where dealership profit actually comes from.
According to the 2025 NADA data Greenfield presented, the average dealership generated $76.6 million in annual revenue, with new vehicle sales accounting for 55 percent.
But revenue tells only part of the story.
Parts and service generate significantly more gross profit per dollar of revenue. That makes improving performance in those departments especially valuable.
The takeaway isn’t to diminish vehicle sales. Selling vehicles creates future opportunities throughout the customer lifecycle.
Instead, Greenfield’s data makes a case for looking across the entire dealership and asking a more focused question: Where can better technology have the greatest impact on the metrics that drive profitability?
Productivity Is the Opportunity
There’s another number that makes that question especially important.
Personnel accounts for 47 percent of the average dealership’s cost structure.
That’s where AI’s ability to automate repetitive work, connect disparate data, and improve employee productivity becomes more than a technology story. It becomes an operating model opportunity.
If employees spend less time gathering information, moving between systems, or completing repetitive tasks, dealerships can accomplish more with the team they already have.
The goal isn’t simply doing the same work faster. It’s increasing revenue and profitability per employee while giving people more time for higher-value work.
And those gains compound.
Greenfield noted that the average dealership generated approximately $2.5 million in net profit before tax in 2025. Because dealership valuations are closely tied to earnings, improving profitability can affect both annual performance and the long-term value of the business.
Move the Metrics That Matter
Of course, technology alone doesn’t turn an average dealership into a top performer.
Greenfield compared average dealership performance with top 10 percent benchmarks across new vehicles, used vehicles, F&I, service, and parts.
No dealership is likely to lead every metric at once.
That isn’t the point.
The opportunity is to identify the metrics with the greatest potential, then use better processes, people, data, and technology to move them consistently.
The right AI solutions, powered by clean, connected data, provide a new set of tools for doing that.
They can automate work that consumes employees’ time. They can also surface insights that help dealership teams make better, more profitable decisions sooner.
The dealerships that benefit most may be the ones willing to be deliberate about where those capabilities can make the biggest difference.
As Greenfield put it, the opportunity is to ask: “For the metrics that we want to move, can we move the needle from being an average dealer to something far out on the right-hand side and do that persistently?”
Fifty years of data show that dealerships know how to adapt.
The next chapter is about what happens when they use AI not simply to keep pace with change, but to improve the economics of the business.
