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AI in Automotive: Separating Fact from Fiction

Dealership accelerating innovation

Breaking down the barriers between AI and the automotive industry, and how it empowers sales and service staff to elevate customer experience.

Despite being a nascent technology with limited public availability in early 2023, generative AI has quickly exploded across nearly every industry in the past year, and automotive is no exception. OEMs and dealers are looking at AI as a lever to reduce the impact of lower profit margins, brittle supply chains, and rapidly evolving consumer behavior.

While some dealers already leverage AI to scale customer engagement, others remain apprehensive about losing human interaction and the perceived difficulties of integrating AI into their existing systems and processes. While these are valid concerns, dealers who complete their due diligence with AI solutions and effectively implement AI are reaping the rewards of delivering a better customer experience.

Impel has been helping thousands of dealers and OEMs of all sizes successfully deploy AI across their ecosystems long before the general availability of ChatGPT and other open-source models. We’ve rounded up the most common AI misconceptions we hear in the industry to separate fact from fiction.

Myth #1: AI replaces sales and service staff

The perception that AI replaces people is as old as AI itself. The reality is far more nuanced. AI is redefining and enhancing sales and customer service roles by automating routine operations and freeing up time for staff to focus on human-centric activities. By handling low-value tasks at scale, AI gives people the breathing room they need to focus on high-value interactions such as building relationships, providing white-glove showroom appointment experiences, and handling the most complex inquiries of highly motivated buyers. 

For example, AI has an increasingly important role in pre-qualifying leads, which has always been an arduous and time-consuming process. By answering detailed VIN-specific inventory, trade-in, and financing questions, AI can distinguish between high-intent buyers and casual visitors. Leads can be scored and qualified in a fraction of the time it would take a sales rep to do so. And it can do it repeatedly and simultaneously with multiple conversations.

The more robust generative conversational AI solutions gather extensive preliminary information and use human-like dialogue to begin developing a relationship. They can even set sales and service appointments for shoppers. Sales reps can then reference customer chat history to prepare for a meeting, bridging the online and offline customer experience gap that buyers experience all too often.

Myth #2: AI is only suitable for automated responses

Dealers have relied on autoresponders for years, which has led many to believe that generative AI is just a next-generation autoresponder. 

In reality, modern generative and conversational AI solutions can go far beyond traditional auto-responder technology. Instead of using pre-scripted answers to common questions, they rely on much newer technology powered by large language models (LLMs) and Machine Learning. This evolution makes AI powerful enough to engage customers from the first lead inquiry through purchasing, servicing, and trading in or selling a vehicle.

Dealers who use a true AI-powered customer lifecycle management platform get the most value out of AI. The common pre-sales use cases like lead response and nurturing certainly accelerate the buying journey, but using AI after the vehicle purchase can maximize a dealer’s most profitable revenue streams. 

Think about it – a busy finance manager doesn’t have time to check in with recent customers to reconsider F&I purchases, and sales reps can’t immediately step away from the sales floor to respond to car-buying leads. Similarly, service reps are stretched far too thin to constantly mine the DMS and contact customers who are due for service. But AI can tap into inventory systems, dealer management systems (DMS), schedulers, and customer relationship management (CRM) systems to send timely and hyper-personalized outreach to customers on their channel of choice.  No marketing software or human being can manage that many touchpoints in the customer lifecycle at the speed, scale, or level of personalization, accuracy, and empathy, as an AI platform can.

Myth #3: AI provides robotic and limited experiences

This notion also stems from the long legacy of scripted auto-responders that have been historically prevalent in the industry, as well associating AI with very narrow use cases (like sending mass emails or providing canned chat and phone responses, for example). While generative AI models are vastly more robust, significant limitations are still evident when generalized or off-the-shelf solutions are applied to very specialized and complex businesses such as automotive retail.

Verticalized AI platforms that are purpose-built for the auto retail industry can handle far more nuanced interactions than an open-source GPT, such as answering questions about vehicle specifications, handling financing and trade-in conversations, and proactively managing the customer ownership experience. 

Impel’s generative AI platform can answer over 11,000 prompts and counting because it uses a proprietary blend of LLMs and learns from over 100 million consumer interactions, continuously exchanging information with the entire dealer tech stack. With industry-specific fine-tuning and guardrails, Impel can protect dealers against unwanted outcomes, provide advanced problem-solving capabilities, follow escalation protocols, and adjust to dealer-specific direction.

Myth #4: Conversational AI will say inappropriate things to customers

One of the most pervasive fears of generative AI is that it’s prone to misinformation. A common shortcoming of open-source LLMs is so-called “hallucinations”, where the model delivers responses that are factually incorrect, nonsensical, or entirely unrelated to the query. Naturally, that’s enough to send shivers up the spines of business owners. The financial and reputational risk of an AI saying inappropriate things, or even worse, committing to faulty pricing or warranty policies is not worth the minuscule gains an open-source point solution may provide.

Verticalized AI platforms equipped with additional control layers and proprietary prompt engineering can successfully mitigate any attempts at ‘manipulating’ or ‘jail-breaking’ conversational AI. Continual testing and training will ensure that the AI will always steer the conversation back towards the desired outcome. 

Myth #5: You can adopt AI effectively without changing your processes

Historically, AI has been perceived as a quick fix to leverage automation in very specific settings, primarily focusing on repetitive tasks and quick responses. Selecting the right AI partner is crucial to ensuring the AI enhances operational efficiency and productivity as intended.

Dealers who deliberately and thoughtfully plan AI deployment will enjoy a smooth implementation that will guarantee success. The most successful AI implementations require two elements of change management that dealers and OEMs can collaborate with AI partners to operationalize: 

  1. Preparing and engaging staff: With always-on technology responding immediately to incoming leads, following up with leads, answering most routine questions, gathering information, and scheduling appointments, the roles and key responsibilities of BDCs, sales, and service team members will evolve in a way that increases their productivity and efficiency. This presents an opportunity for staff to think about their roles differently, and use their newly freed up time to nurture hot leads, make phone calls, close deals, and manage showroom and service appointments, all while giving high-value customers white-glove treatment. Many dealers also evolve their staff’s compensation and incentive structures to more effectively incentivize higher-order behaviors and performance metrics now that the staff is working alongside AI.
  2. Integrating dealer systems: Integrating AI into dealer systems overcomes several misconceptions we’ve touched on about AI in automotive. Without making these connections, AI is nothing but a conversational tool that neither answers customers’ questions nor drives toward automotive retail-specific outcomes. Inventory systems help AI answer VIN-specific questions down to the finest detail. CRM connections keep an accurate record of what the AI discussed with a lead, what the status is, and everything a sales rep needs to know prior to meeting a lead in person. Moreover, it keeps the engagement going after the sale by mining the DMS for service retention and F&I opportunities.  Bypassing this step in implementation is a leading factor of limits the value (and time to value) of automotive AI.

Using AI in automotive sales and service requires a new approach combining the principles of continuous improvement and change management. Companies like Impel that provide industry-specific solutions can partner with dealers to help them smoothly implement change, modify processes, train employees, and reduce friction during this period of change.

Impel CEO Devin Daly hits on the key AI implementation pitfalls dealers face that fuel misconceptions on AI performance.



Making the best decision for your business

Early AI adopters have set themselves apart from dealers who are still relying on pre-scripted chatbots and auto-responders at the most critical phases of the car buying and ownership experience. But it’s no longer for early adopters – AI is widely available and will soon be essential to meeting consumer expectations and achieving sustainable business growth across all areas of the dealership ecosystem.

Impel is the industry’s most advanced AI-powered customer lifecycle management platform, providing everything you need to deliver better experiences at every touchpoint of the customer journey. Book a demo today to learn how Impel can transform your business model for the new era.