In Salt Lake City, a documented car purchase involved AI agents negotiating on both buyer and seller sides: an employee of the Utah dealership Mark Miller Subaru spent nearly four hours discussing price offers, financing options and bespoke terms — and only afterwards discovered the counterpart was not human. The episode highlights that AI agents are already active players in global automotive retail.
A digital gap in the Hungarian market
At the same time, a case study by 4YES Kft. shows that a large portion of the Hungarian car retail sector still relies on 2010s-era software and manual Excel spreadsheets. International studies nevertheless point to measurable benefits from AI-driven systems: the Fullpath Auto Intelligence Index (April 2026) reports a 37.3 percent increase in conversions and a 14.8 percent reduction in lead costs for operations using AI tools.
Case study: a fifty-year-old Hungarian dealer
One partner of 4YES is a Hungarian brand dealership with more than fifty years of history. In February 2026 the dealer began a project to implement an AI assistant — a lead-management and offer-generation module intended to receive emails, interpret customer queries and recommend models.
The rollout stalled not because of lack of intent, but due to the absence of a CRM and task-management system that would fit both automotive sales workflows and the AI assistant’s need for structured data. According to 4YES, simply automating existing Excel processes was insufficient: the core workflows had to be rebuilt. With manual tables and fragmented data, adding an AI layer would have carried an unacceptable risk of error.
Build the foundations first, then add AI
In 4YES’s implementation the lead pipeline, offer generation and status tracking were consolidated into a unified, real-time interface. Only after this foundation was in place did they attach the AI layer, which could then operate on structured, consistent data.
Todd Smith, CEO of QoreAI, expressed a similar sequence in an interview with CBT News on May 20, 2026: companies should first establish the internal "dealership brain" — the data, process and transaction layer — and only afterwards deploy AI assistants.
The real question: what will you build your next five years on?
The Salt Lake City AI–AI negotiation and a Hungarian dealer’s Monday-morning Excel routine may look like different universes, but they are two ends of the same issue: how participants plan their next five years. 4YES’s experience indicates that Hungarian dealers should prioritise restoring operational fundamentals so that AI can perform meaningful work.
"Our goal is not to sell AI. Our goal is to let dealers focus on customers again, not on forms. AI is only a tool for that," summarized Horváth Emese of 4YES.
Conclusion
AI can already substitute human actors in some negotiation processes, but for the technology to function reliably in Hungarian car retail, digital foundations — unified CRMs, real-time interfaces and clean data flows — must come first. The 4YES case demonstrates that embedding AI without first rebuilding internal processes is unlikely to deliver lasting results.
