Artificial intelligence (AI) is dominating headlines across the automotive retail sector, but for dealerships, adopting the technology is only the beginning. On the latest episode of Inside Automotive, Greg Uland, Vice President of Marketing at Reynolds and Reynolds, joins us to explore how successful AI adoption starts with a problem that needs solving.
According to Uland, dealerships have no shortage of problems to solve, from flat industry growth and rising labor costs to increasingly complex daily operations. He recounted that a dealer he recently spoke with said labor costs had increased by 40% over four years while output remained effectively flat.
Unified data = AI success
Uland said that deploying AI tools without unifying underlying dealership data creates major operational risks. When systems operate in isolated silos, employees waste hours transferring and verifying information across platforms. As Uland put it, AI can “do the wrong thing fast.”
“For [dealers], it seems like it always starts with a problem, right? Something they're trying to solve. They aren't just turning on a new tool because it's neat technology… they have a problem they're trying to solve. And that's the starting point.”
Additionally, Uland emphasizes that building a single, unified data layer behind AI tools serves as the foundation for effective execution. A single intelligent agent with access to complete dealership data, he said, can deliver greater business value than an army of disconnected chatbots trained on limited information.
Generative AI vs. agentic AI
According to Uland, dealers need to understand the evolution of AI to aid in better planning their technology roadmap:
- Generative AI: Functions like an eager intern that assists with daily tasks, such as drafting customer emails, taking meeting notes, or summarizing data while humans still execute the primary work.
- Agentic AI: Represents the next wave of technology that actively participates in operations, orchestrating complex workflows, taking automated action across systems, and driving faster business decisions.
The shift, Uland said, is from AI that assists with tasks to AI that participates in daily dealership operations.
Further, software alone cannot transform a business without intentional changes in daily human behavior. To maximize return on investment, dealership leaders must shift how their teams make decisions and manage routine workflows.
As development cycles shrink from years down to days, software providers iterate tools rapidly based on dealer feedback. Uland said the rapid pace of development is already changing how software providers respond to dealer feedback, allowing tools to evolve in days or even hours rather than months or years.
