AI Agents: The Best Rebrand Since Mayo and Aioli

AI agents are making a big splash, touted on LinkedIn by influencers as the next big thing. But here’s the simple truth: they’re not exactly new.

Like the upgrade of mayo to aioli, the concept has been around for years; they added some acid and spice, gave it a shiny new label and all of a sudden it’s the hottest topic in tech. So, what exactly are these AI agents, and why should you care?

Let’s break it down.

Agent, AI Agent

At their core, AI agents are autonomous systems that analyze data, utilize LLMs to make decisions based on that data, and then automatically perform tasks—like answering questions, personalizing experiences, or automating processes. They keep learning and adjusting over time to get better at what they do, often working in real-time to deliver results.

For car dealerships, AI agents can act as virtual assistants that engage website visitors live—answering questions about vehicles, financing, or dealership services. They can also assist your sales team by analyzing customer data to recommend personalized vehicle options, schedule appointments, and even handle follow-up automatically. Think of them as digital helpers with a mind of their own—understanding what’s happening behind the scenes, making choices, and taking action without you needing to micromanage.

From virtual assistants to complex recommendation engines, AI agents come in many forms and sizes. They monitor customer interactions, respond to questions, automate repetitive tasks, and even predict what shoppers might need next.

Just a Rebrand, Right?

Now that we have the basics, let’s look under the rebranded label and understand what we are looking at:

We have been using automation and simple AI for years, but calling it an “agent” or an “agenetic system” gives it a fresh identity that recognizes how much more capable, autonomous, and scalable AI has become. Think back to mayo evolving into aioli: same core ingredients, just a richer, more refined version.

Today’s AI agents aren’t just tools, they’re proactive partners that can anticipate needs, make decisions, and act on their own. The secret to their success is data, where the more high quality data they have, the smarter they get. That’s where an AI-first Customer Data Platform (CDP) can prove helpful. Acting as the ‘brain,’ for an AI agent, a CDP consolidates all your dealership’s customer data into clear, real-time profiles, giving your AI agents the context they need to personalize experiences, recommend vehicles, and automate tasks seamlessly.

Consider this: A customer browses your website, looks at a specific SUV, and interacts with the chatbot. Thanks to your integrated CDP, the AI agent knows about this buyer’s past inquiries, preferences, and previous visits. It can then recommend similar vehicles, suggest financing options, or even schedule a test drive, all done automatically, and all personalized based on that customer’s real-time data.

The AI Assembly Line

One reason AI agents feel so ‘new’ and smarter these days is the rise of Large Language Models (LLMs) like GPT-4. These models enable AI to understand and generate human-like language, making conversations more natural and engaging. Instead of canned responses, an AI powered by an LLM can interpret complex questions like, “What are the best family SUVs under $30,000?,”and respond with detailed, tailored answers.

A mistake many make when they are using an LLM is feeding the AI a long, detailed prompt and pressing go, hoping it figures it out without missing anything, producing errors, or hallucinating. When a prompt is too complex, the AI simply gets overwhelmed. To create functioning AI agents, it’s all about how you structure your prompts and how much you expect a single LLM to produce.

Imagine you have a new employee joining your team. Instead of giving them all the information they need to understand the entire workings of your dealership you offer only the context they need for a particular task you need them to perform. This reduces overwhelm and sets very clear expectations for their performance. When you do this with multiple ‘employees,’ each of whom specializes in one specific task, you create a multi-agent architecture.

Instead of one LLM trying to do everything, you create specialized helpers, each with a clear, simple task working together like an assembly line. One agent might handle tracking inventory, another writes ad copy on the available agent, and another ensures messages stay within character limits. Each focuses only on what they need to do, reducing mistakes and keeping the process more accurate.

Building Agentic Dealerships

In the dealership context, AI agents can act as virtual reps, holding informed, natural dialogs with potential customers, offering personalized recommendations, and handling diverse questions without bringing a human in the loop. It results in fewer missed opportunities, better experiences for your shoppers, and a smoother process for your team.

While the terminology might be new, the idea isn’t. What has actually changed is the scale and sophistication of these systems. Dealerships that actively leverage their data through AI agents are already seeing better engagement, higher conversion rates, and more efficient operations and, because AI agents keep learning from new data, they only get smarter over time, creating more opportunity for business growth.

An Effective Evolution

Just like mayo evolved into aioli, AI agents have gotten a sleek marketing facelift. But underneath, they’re the same smart systems, now fueled by real-time, activated data. This rebrand signals a shift toward more autonomous, personalized, and efficient engagement that can help your dealership deliver deeply personalized, timely experiences that customers expect today.

Looking forward, AI agents are poised to redefine the way we work, shop, and communicate, turning the concept of 'smart' from an exception into the new standard. Embracing this evolution now will position your dealership ahead of the curve, capable of delivering experiences that truly stand out in a competitive market.

Ilana Shabtay
VP of Marketing at Fullpath