While many dealerships are experimenting with generative AI, most are only scratching the surface of what the technology can deliver. Joining us on today’s episode of Driving Solutions are Chief Marketing Officer at Lotlinx, Kerri Wise, and GM of Product and Technology at Lotlinx, Lance Schafer.
A recent Lotlinx survey found that roughly 80% of dealers use generative AI tools on a weekly basis, as Wise confirmed. Despite this adoption, the primary use cases remain concentrated in sales and marketing functions, signaling considerable untapped potential across dealership operations.
“We saw 84% of dealers reporting to us that they were often or almost always get a failure in terms of what they get out of generic AI tools.” – Kerri Wise
Both Wise and Schafer emphasized that the meaningful impact of AI depends on integrating these systems with dealership data. Connecting tools to sources such as CRM platforms, inventory systems, sales performance metrics, and analytics platforms enables contextual insights and reduces inefficiencies associated with manual data entry. They believe that fully connected systems allow AI to analyze multiple data streams simultaneously, improving decision-making and operational visibility.
However, reliance on general-purpose AI tools continues to present challenges. The survey showed that 84% of dealers frequently experience ineffective or unusable outputs, as Wise expressed. Common issues include generic responses, a lack of dealership-specific context, and limited capabilities to address operational questions such as inventory performance or vehicle-level strategy.
“[For early dealership AI adoption] We’re seeing kind of these initially agentic kind of things like writing descriptions for the website or to be distributed into the portals or taking a look at images and redoing them or annotating them to be more effective on the websites or when they distribute.” – Lance Schafer
These limitations are driving demand for more specialized AI solutions tailored to automotive retail. While dealers are increasingly seeking tools that can diagnose inventory challenges, identify underperforming vehicles, and recommend actionable steps to improve sales outcomes.
Lotlinx’s platform, LotGPT, now serves around 6,000 dealer users, with early trends suggesting that dealers first explore competitive positioning and market comparisons. Over time, they transition to more in-depth operational analysis, focusing on inventory management, merchandising enhancements, and VIN-level insights to identify reasons why certain vehicles remain unsold.
The technology is also evolving beyond analysis into execution. Emerging use cases include automated content generation, image enhancement, and data-driven merchandising adjustments. These capabilities reflect a broader shift toward systems that interpret data and act on it.
Looking ahead, Wise and Schafer stated that AI is expected to transition from a support tool to a more autonomous role within dealership operations. Near-term adoption will likely include human-in-the-loop models, where AI generates recommendations or completes tasks requiring managerial approval. In the long term, AI systems are expected to handle more functions independently, from pricing adjustments to operational workflows.
As dealerships continue to adopt and refine AI strategies, the focus is shifting from experimentation to measurable business outcomes. The next phase of adoption will center on using AI to deliver actionable insights, streamline operations, and improve overall dealership performance.
