NADA is where long-term technology decisions get made.
Every year, dealers walk the show floor looking for solutions that will shape their operations for years to come. And this year, like last year, AI will be everywhere. Every booth will have an AI story. Every demo will feature some version of “powered by AI.”
But the more AI dominates the floor, the harder it is to find clarity. When everyone claims to offer AI, how do you know which solutions are built for automotive and actually effective, and which are just generic tools with a new label? When every vendor promises transformation, how do you separate platforms from point solutions?
This guide reflects what we’ve learned as we’ve worked with thousands of dealers and OEMs across the globe to implement Automotive AI.
The Problem With Evaluating AI at Trade Shows
Walk the floor, and you’ll see AI everywhere. But look closer, and the picture gets murkier. Many vendors still sell isolated AI tools. Others repackage outdated chatbot technology with a fresh interface. None solves system-level operational challenges, focusing instead on surface automation: a widget here, a scripted response there.
Some vendors even claim sophistication while being overly reliant on generic, open-source models with little specialization for automotive. That’s a risk. Without industry-specific training and automotive guardrails, these tools can hallucinate, go off-brand, or simply miss the nuances of how dealers actually operate. What looks impressive in a booth can quickly become a liability in your showroom.
Short Demos Can’t Tell the Full Story
A 10-minute demo is a great handshake, but your dealership needs a long-term partner. It’s easy to make a chatbot look smart for thirty seconds; it’s much harder to keep a lead engaged through months of automated, context-aware follow-up.
At NADA, use the demo to see the “wow” factor, then use the conversation to press on how the downfunnel workflow operates. A demo might show a single flawless response, but you need to know what happens when a customer goes silent for a week, asks a complex question about out-of-state titling, or changes communication channels. The real impact of AI is in orchestrating the entire lifecycle—how any vendor manages the non-linear customer journey from the first website click to the service bay and back again. Look for the tech that works as hard as your team does and handles industry-specific nuance, even when the show floor lights go down and the service bays are closed.
Start With the Right Question: Is This AI Built for Automotive?
Why Vertical AI Matters in Automotive
General-purpose large-language models (LLMs) excel at language tasks. It can write, summarize, and hold a conversation. But automotive environments require execution, not mere responses. Dealers don’t need AI that can describe the merits of leather interiors—they need AI that checks real-time VIN-specific inventory, understands financing options, guides trade-in processes, understands OEM build data, and moves a customer toward a showroom or service appointment.
Vertical AI that’s designed for automotive retail incorporates industry context and workflows. It knows that a lead from OfferUp needs a different approach than one from Edmunds. It understands when to surface trade-in options versus lease specials. It is oriented to drive dealer-specific outcomes. This enables consistent action across the customer journey by combining the power of foundation models with the accuracy, precision, and guardrails of verticalization and deep ecosystem integration.
What to Look for on the Show Floor
- AI that was trained on automotive data
- AI that enables dealer and OEM brand customization and tailoring
- Proven performance in real dealer environments. Think agentic deployments at scale, not just pilots or single-store tests.
- Clear examples across marketing, sales and service journeys
- Advanced industry-specific controls, safety and reliability to prevent misuse, abuse, and hallucinations, and for successful outcomes
Look Beyond the Demo: How AI Fits Into Your Tech Stack
Siloed technology creates friction. When systems don’t talk to each other, your team wastes time copying data between platforms rather than engaging with customers.
AI should connect to and activate data from your existing systems. Your CRM, DMS, digital retailing platform, website, inventory feeds, and service tools (schedulers, marketing solutions, etc.) all need to work together. If the AI can’t access your inventory in real time, or doesn’t know a customer’s service history, it’s operating with one hand tied behind its back.
So as you walk the floor at NADA, that’s what you should be evaluating: not just whether a solution has the right features, but whether it fits into the way your dealership already operates across the buying and ownership journey.
Questions Dealers Should Ask Vendors
Come with specific questions. How does this integrate with our current platforms—CRM, DMS, inventory feeds, and scheduling software? What data does the AI access in real time? Can it coordinate actions across channels, whether that’s web chat, SMS, or email, and does it recognize each customer’s preferred way to communicate?
Ask about customization; can you configure the AI to match your brand voice? Does it support OEM and dealer compliance requirements, including policy guidelines and content filters? If the vendor hesitates or speaks in generalities, dig deeper.
Security, Safety, and Reliability
Ask about security and compliance. AI that communicates directly with your customers is a liability if it isn’t built with guardrails. Generic models hallucinate. They go off-brand. They say things no salesperson ever would.
Look for platforms with safeguards specifically designed to mitigate jailbreaks and hallucinations. Ask about enterprise-grade security—SOC 2, TCPA, CCA, GDPR compliance—and clearly defined infosec and data privacy processes. If a vendor can’t speak to these specifics, that’s a red flag.
Why Agent-Based AI Changes the Conversation
Instead of handling a single task (as chatbots do), Agent-based AI coordinates multiple activities simultaneously and autonomously. Different agents manage the entire customer lifecycle, from first inquiry through purchase and into service retention, adapting their approach based on where each customer is in their journey.
And AI agents don’t replace people; rather, they ensure consistency and follow-through when your team can’t be everywhere at once. If a customer submits a lead at 11 PM, an agent responds immediately. If that same customer goes quiet for five days, then re-engages with a question about a different vehicle, an agent picks up the thread with seamless continuity and context. Your salesperson walks in on Monday morning with context and an appointment rather than a cold lead.
Every customer interaction is supported, whether it happens at 2 PM or 2 AM.
Evaluating Real Business Impact, Not Buzzwords
AI should improve lead response, appointment rates, show rates, and service retention. It should also drive operational efficiency by reducing hours spent on manual follow-up and reliance on BDC headcount. If a vendor can’t speak specifically to these areas, that’s a red flag. And if they can speak to them, ask for proof. Request performance data. Ask for real outcomes, such as increases in close ratios and appointment set rates, reductions in response time, and improvements in completed repair orders and service retention.
Look for evidence beyond pilot programs. A solution that works for three months at five dealerships is different from one that’s been running at scale for years.
The Role of Operating Systems in Automotive AI
Why Point Solutions Fall Short
Dealers run complex ecosystems. Between your CRM, DMS, inventory feeds, OEM systems, schedulers, digital retailing platform, and marketing tools (and more!), your team might log into ten different systems before lunch. Each one holds a piece of the customer picture, and none of them sees the whole thing. These disconnected tools slow teams down. Worse, they create gaps where customers fall through the cracks.
The Value of an AI Operating Layer
Instead of another tool, an AI operating layer provides a unified view of the customer journey, enabling consistent execution across every touchpoint. It unifies, cleanses, and actually activates customer data across the journey, coordinating intelligence across the entire tech stack. Because it integrates with your existing systems, it can deliver true personalization. Every interaction is informed by that customer’s history, preferences, and intent.
The best part? It scales without adding staff pressure. Your team doesn’t need to work harder. The operating layer handles the coordination so they can focus on closing deals and building relationships.
How Dealers Can Prepare Before Walking the Floor
The most productive conversations at NADA start before you arrive.
Define your success criteria in advance. What problems are you trying to solve? What does a successful AI implementation look like for your dealership in 12 months? If you can’t articulate that before the show, you’ll be swayed by whoever has the best demo.
Map your current systems and gaps. Know what’s working, what’s not, and where the friction points are in your customer journey. This clarity helps you evaluate whether a vendor’s solution fits your needs, or just sounds good in a booth.
Also, prioritize long-term fit over short-term features. A flashy capability that doesn’t integrate with your tech stack creates more problems than it solves.
Use NADA to validate your strategy, not to start from scratch. And research the companies you want to speak with beforehand. You’ll ask better questions, spot the gaps faster, and make better use of your time on the floor.
Making NADA Count Beyond the Handshake
NADA is where direction is set. The AI decisions made this February will shape how leads are handled, how customers are engaged, how service retention is managed, and how your team spends their time.
That’s not a decision to make based on a 10-minute demo.
Forget promises and really evaluate the platforms. Ask the hard questions. Demand real data. And look for partners who understand that automotive is a business with distinct workflows, customer journeys, and demands.
Agentic AI offers a path forward built for the reality of automotive retail. The question is whether the vendor you’re talking to has built for it.