The customer journey in the used car market involves so many loops and bends that it often leaves buyers frustrated and automotive dealers with a low conversion rate. Lack of transparency in pricing, unclear vehicle history and financing hurdles mar the experience – making it far less seamless than buying a new car.
Lack of trust remains a critical barrier. A Gallup survey places car salespeople among the least reliable professionals, with only eight percent of respondents rating them high on honesty and ethical standards.1 Opaque and fractured processes compound this trust deficit, further deterring buyers.
Progress is being made, with many dealerships streamlining processes to overcome this challenge. A leading used vehicle marketplace consolidated and standardized business processes across contact centers, auction operations, finance and accounting, human resources and IT. The digital-first operations delivered a consistent, high-quality Customer Satisfaction (CSAT) score of 85-95 percent, while significantly lowering operational costs.
The next frontier is already here: Agentic AI. By embedding autonomous Artificial Intelligence (AI) agents into the used car marketplace, dealers can fundamentally re-shape Customer Experience (CX) in buying and selling. Unlike traditional chatbots that merely share eligibility criteria, an AI agent can go further – verifying documents, matching buyers with the right financing plan and booking a test drive end-to-end, without human intervention.
The potential extends across the entire value chain – lead qualification, dynamic pricing, fraud detection, regulatory compliance and post-purchase engagement. Agentic AI doesn’t just remove friction, it builds transparency and trust, creating a differentiated advantage in an industry long plagued by inefficiency and skepticism.
Why Traditional Buying-Selling Models Fail
The used car market may be massive, but its traditional buying and selling models are increasingly unable to meet the expectations of digitally savvy customers. Structural inefficiencies, shifting consumer behaviors and heightened competition from digital-native entrants have exposed the gaps in the legacy approach.
Key challenges include:
Market Fragmentation
The US and European used car markets together generated USD 1.2 Trillion in revenue in 2023, yet remain highly fragmented. With the top 20 players controlling less than 20 percent market share in the US and under 10 percent in Europe, digital innovation has been slow, leaving incumbents vulnerable to new-age players.2
Digital-native Competition
New-age players have proven that customers are willing to purchase high-value assets online if the experience is transparent, seamless and personalized, setting a higher benchmark for incumbents.
Evolving Consumer Behavior
Today, 95 percent of used car searches begin online and more than 70 percent of buyers compare prices across third-party platforms. This shift demands digital-first, on-demand experiences, including algorithm-driven pricing, seamless browsing and multi-location delivery – something that traditional models struggle to deliver.3
For CXOs across dealerships, equipment manufacturers, financial providers and marketplaces, the implications are clear – the traditional car-buying and selling model is broken. Without trust, transparency and digitally orchestrated customer journeys, incumbents will struggle to compete against disruptors who are already defining the new standard.
From AI to Agentic AI: A Step-Change in CX
Where traditional AI has been the co-pilot to human agents driving CX, agentic AI is set to take the driver’s seat. Automation tools, such as chatbots, scripted virtual assistants and recommendation engines, have made customer interactions faster and cost-to-serve lower. However, they have not solved the deeper problems of trust, transparency and friction.
Agentic AI marks an inflection point in that journey. Unlike traditional AI, which reacts to prompts, agentic AI is designed to act with intent, autonomy and adaptability. It does not just process data, it understands context, sets goals and executes actions to move the customer toward resolution.
Five Core Capabilities that Set Agentic AI Apart
When applied to the used car marketplace, these capabilities are transformative.
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Buyers no longer need to wade through stale listings or confusing financing options. Agents can deliver personalized recommendations, dynamic pricing and verified vehicle histories in real-time.
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Sellers are spared the tedious tasks of managing unqualified leads and repetitive queries. AI agents can automatically validate documents, optimize listings and manage bidding processes.
What was once a disjointed operation, low on trust, a streamlined and transparent function with engaged customers.
Agentic AI Across Customer Journey Stages
From the time a lead enters a dealer’s portal to the vehicle handover, AI agents can manage interactions end-to-end. Where the traditional process relied on manual validation, back-and-forth calls and stressful negotiations, agentic AI brings:
What does this look like in practice?
Consider Cathy, a 38-year-old marketing manager who loves upgrading her cars but dreads the selling process. Usually, she would spend hours uploading ownership documents, waiting for approvals and second-guessing opaque pricing models, often abandoning the process out of frustration.
With an AI-powered virtual agent, Cathy’s journey looks very different. Her documents and images are verified instantly, a vehicle condition report is generated automatically and her seller profile is created seamlessly. Instead of chasing information, Cathy is guided step by step with personalized prompts, gaining confidence and clarity along the way.
The outcome is a win-win: Cathy completes her sale smoothly, while the marketplace sees measurable gains. Our projections show that such transformation can reduce bounce rates by 15-20 percent, increase seller conversion from 35 percent to 75 percent and shorten sales cycles from 21 days to 12.
5-Year Outlook and Strategic Recommendations
Agentic AI is set to draw a firm line between leaders and laggards in the used car marketplace. The next 5 years will determine which organizations seize competitive advantage and which are left behind.
Strategic Imperatives for Automotive and Used Car Industry
To secure advantage, leaders must act with urgency. The path forward is clear:
Owning the Future of CX
Few industries test customer patience like the used car marketplace, where friction and distrust have long been the norm. Agentic AI changes that equation entirely. It is not another layer of automation but the foundation for a new CX model – one where trust, speed and personalization determine who wins and who fades into irrelevance.
Over the next 5 years, the decisive factor in this sector will not be inventory or pricing power, but CX as orchestrated by agentic AI. Customers are already choosing marketplaces for the confidence and seamlessness of the journey they provide, and this trend will only accelerate.
Agentic AI will inevitably re-define automotive CX. The opportunity lies in deciding whether to lead that shift by designing journeys built on trust and personalization, or risk being constrained by outdated models.
Talk to our experts to evaluate how agentic AI can re-imagine your customer experience and position your business for lasting advantage.
References
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https://news.gallup.com/poll/608903/ethics-ratings-nearly-professions-down.aspx
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https://www.mckinsey.com/industries/automotive-and-assembly/our-insights/data-and-analytics-in-the-drivers-seat-of-the-used-car-market
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https://www.mckinsey.com/industries/automotive-and-assembly/our-insights/data-and-analytics-in-the-drivers-seat-of-the-used-car-market
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https://www.gartner.com/en/newsroom/press-releases/2025-03-05-gartner-predicts-agentic-ai-will-autonomously-resolve-80-percent-of-common-customer-service-issues-without-human-intervention-by-20290
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https://www.mckinsey.com/~/media/mckinsey/featured insights/artificial intelligence/notes from the frontier modeling the impact of ai on the world economy/mgi-notes-from-the-ai-frontier-modeling-the-impact-of-ai-on-the-world-economy-september-2018.ashx