A quick method to log opportunities that don't come from forms or portals and stop them disappearing from the funnel.

What AI can bring to sales, buying, stock, marketing and customer service at a dealership or used car dealer.

Data architecture so the agent answers with correct information and updates the sales process.

Why the vehicle of interest should be part of the opportunity and how to handle changes, alternatives and cars already sold.

AI at a dealership is not a future project: it is a set of specific tasks that can be automated today. The problem is not whether AI can help, but choosing where to start. This article organises 25 real cases by business area, explains what AI does in each one and provides a criterion for prioritising them without spreading yourself too thin.

Practical differences between answering questions and getting work done inside the DMS.

What Faconauto is, who it represents and how the employers' association that brings together Spain's official dealership associations works.

Which features add value for a small used car dealer and which add complexity without improving sales.

The most common mistake when implementing AI at a dealership is not choosing the wrong tool: it is starting without a specific problem. "I want to use AI" is not a valid starting point. "We have 40 leads left unanswered every weekend" is. This article explains the method for going from that specific statement to a controlled pilot, with metrics, an owner and without stopping operations.

The AI sales agent doesn't close deals: it prepares the ground so the salesperson can close them. It answers the lead in seconds, finds out what the buyer is looking for, filters the stock and proposes an appointment. When negotiation or complexity comes up, or the buyer asks to speak to a person, it hands the conversation to the salesperson with a structured summary of what it already knows. This article explains how that split works and how to measure it.

Design the CRM around the salesperson's actual work to avoid incomplete data and turn it into a daily help.

An AI agent is not a chatbot that answers frequently asked questions or an automation that always runs the same sequence. It is a system that receives a goal, interprets the context of the situation, chooses from a set of permitted actions and leaves a traceable result. That difference matters because it defines what it can do on its own, what needs approval and what it should never do without a person.