A second-brain approach uses artificial intelligence to automate tasks you currently perform and reduce cognitive load. I attempted this earlier this year for tasks such as site selection, preparing car wash studies, and opinion of value.
What took me weeks to complete 20 years ago, I can accomplish in two days with keystrokes and voice commands. In other words, AI has greatly augmented what I do but not yet replaced me.
I asked AI about that possibility. Specifically, “how will the U.S. car wash industry be affected if site selection for new washes became fully automated, AI-driven, data-first, and standardized?”
AI said the effects would ripple through the industry in ways that go well beyond just better locations. It would fundamentally reshape competition, consolidation, and even the risk of overbuilding.
Site selection is a partly subjective, experience-driven process that involves assessing and evaluating traffic, visibility, zoning, competition, lot geometry, and other site location factors. A fully automated process would enable more consistent A-tier site identification, faster underwriting and decision-making, and less reliance on local expertise.
Consequently, chains could scale more quickly, start-ups could compete more intelligently, and there would be fewer bad bets on poor locations. As a result, there would be a higher average ROI per site (at least initially).
However, if everyone uses full AI automation, there would be convergence. Algorithms would identify the same high-traffic corridors, underserved trade areas, and demographic sweet spots. In other words, everyone would be chasing the same identical things.
This would cause markets to fill up faster, increasing competition and customer acquisition costs. The net effect would be a decrease in profitability per site.
If AI identifies the best sites, landowners stand to gain leverage because prime parcels will become obvious to everyone and will most likely trigger bidding wars. Here, big companies will win because they can move faster, have cheaper access to capital, and are willing to overpay in the short term for long-term network value.
As a result, land costs will rise, and smaller operators will be squeezed out of prime locations. Full automation would remove the biggest advantages of independent operators: local knowledge and intuition. Consequently, chains would gain a significant edge through standardized site selection, operations, and portfolio optimization across regions.
Arguably, once everyone has good locations, location is no longer a strong differentiator, and competition would shift to performance, brand image, and density.
AI automation may also pose a risk of systematically overestimating demand because it relies on similar datasets optimized for key performance indicators such as traffic, income, and density. This may result in too many washes being built in the same trade areas, cannibalization of sales, and declining same-store sales.
According to AI, fully automated site selection would make the industry more data-efficient but less profitable per unit over time while concentrating power in larger operators.
Do we have to worry about this prognosis? According to AI, the answer is yes, eventually. The industry does not need 100 percent automation. Once automation reaches 75 to 80 percent, the advantage of human intuition will collapse. This is the tipping point where everyone finds similar sites, returns compress, and overbuilding risk spikes.
I asked AI for the most likely scenario and the probability of its occurrence. The answer: if 60 percent or more of new builds adopt automation site selection, there is a 60 to 80 percent probability that second-order effects would occur within the next 10 years.
However, the probability would be affected by technology innovation, adoption rates, and con-straints such as real-estate bottlenecks, differentiation, and model diversification.
Bob is an industry consultant with more than 25 years of experience and is a former operator of car wash, oil change, and detail businesses. He can be reached at (727) 723-9474 or bobr427@protonmail.com.