Used cars vary widely in condition and history, even for the same model. The transaction process is complex and filled with technical terms, creating a high barrier to entry. Consumers have had to make purchase decisions based on limited information. Signs of change are now emerging in this entrenched used car market, driven by the gradual adoption of artificial intelligence (AI) across the entire used car transaction process. Based on massive datasets, AI precisely analyzes vehicle condition, improving diagnostic accuracy and simplifying the complex search process. It also adds vehicle recommendation functions to support more rational consumer choices.

Automation of diagnostics… Decisions based on ‘data’, not ‘experience’

The accuracy of used car diagnostics is directly linked to consumer trust. Traditionally, assessing the condition of a used car depended heavily on the inspector’s level of experience and subjective judgment. With the introduction of AI to platforms, image analysis technology is making the diagnostic process more systematic and structured. Options and key specifications are automatically recognized from exterior and interior photos alone, and large-scale training data are used to minimize errors.

In particular, AI technology capable of analyzing tens of thousands of vehicle images in a short time enhances not only diagnostic efficiency but also the consistency of information. It standardizes criteria that could vary by person through data-driven algorithms, thereby improving the reliability of core information that is directly tied to used car price formation. There are now cases in which AI recognition results are prioritized over human judgment, and this approach is reshaping diagnostic processes across the board.

For example, Encar.com, which operates the largest used car platform in Korea, has developed “Encar Vision AI” using the company’s extensive vehicle transaction and image data accumulated over 25 years. Tasks that had relied on people—such as entering vehicle information, inputting options, and registering vehicle photos—have been automated using AI, eliminating repetitive and time-consuming work.

Because each used car is different in condition and history, large-scale training data are essential to ensure reliable diagnostics. Based on these data assets, Encar.com has continuously advanced its image analysis and recognition algorithms.

As a result, Encar.com developed Encar Vision AI, which analyzes exterior and interior images of vehicles to automatically identify options, models, and key feature information. This technology, which can analyze tens of thousands of vehicle images in a matter of seconds, plays a role in improving the accuracy and reliability of the most important information in used car transactions—vehicle condition.

Encar.com named its proprietary vision AI technology “Mobile Diagnostic AI” and deployed it to more than 60 Encar Diagnostic Centers nationwide. Each Encar Diagnostic Center uses Mobile Diagnostic AI to review information on vehicles submitted for Encar Diagnostics.

When Mobile Diagnostic AI is used during vehicle inspections, the system can automatically recognize specifications such as grade and major options using only interior and exterior photos. By prioritizing AI recognition results over human judgment for key information that substantially impacts used car pricing, diagnostic accuracy has been significantly improved.

According to Encar.com’s own survey, Mobile Diagnostic AI can currently recognize about 1,700 used car models with an accuracy rate of over 99%. It is continuously learning new models and options. Leveraging Mobile Diagnostic AI, Encar.com conducts diagnostics on approximately 400,000 vehicles per year across its nationwide Encar Diagnostic Centers. At present, “Encar Diagnostics” vehicles account for about 70% of the listings regularly registered on the platform.

AI chatbots and vehicle recommendation assistants that shorten used car search time

The way used cars are searched is also changing as AI services become more sophisticated. In the used car purchase process, the stage where consumers spend the most time is “comparison and search.” The traditional structure, in which consumers had to manually compare year, mileage, price, and options one by one, created a high barrier to entry.

AI chatbots and recommendation systems recently introduced on used car platforms are turning this process into a conversational interface. They respond to questions by reflecting listing-specific condition and warranty information in real time, and they gradually refine conditions through natural language-based dialogue. This is particularly useful for consumers with limited automotive knowledge, enhancing information accessibility while reducing search time.

For instance, Encar.com was the first among domestic used car platforms to introduce “Encar Mitzgo AI Chatbot,” which is based on dynamic prompt generation. The Encar Mitzgo AI Chatbot uses Google’s latest AI model, Gemini, to analyze and combine individual data on approximately 40,000 Encar Mitzgo vehicles in real time, providing listing-specific customized responses. This is regarded as an advanced technology because it does not simply retrieve information from a database, but generates answers by simultaneously analyzing real-time listing information and the context of user questions.

For example, a user considering a particular vehicle on Encar.com can ask the AI chatbot natural language questions such as “How much engine and transmission warranty is left?” or “What is the condition of the consumable parts?” The AI immediately analyzes the latest condition data of the listing and responds in a format such as “Warranty remains for 1 year and 6 months or up to 70,000 km” and “Tire tread depth is 10 mm and in good condition.” This reduces the need to navigate through complex reports or multiple pages, providing greater convenience.

The AI-based “vehicle recommendation assistant” is another service that alleviates the burden of the used car search process. Users can narrow down desired conditions conversationally through a natural language-based “search by talking with AI” function. After setting basic conditions such as budget and vehicle type, they can further refine their preferences through dialogue with the AI and receive recommended listings accordingly.

AI chatbots and recommendation systems help even consumers with limited automotive knowledge easily understand vehicle information and quickly find a car suited to their needs amid a vast pool of listings. In this process, they not only improve the efficiency of used car searches and access to information for consumers, but also are expected to bolster trust in used car platforms.

An Encar.com representative said, “AI is a core strategy that enhances trust in the used car market and strengthens the fundamental competitiveness of the platform,” adding, “Through an all-encompassing AI transformation that covers transaction services and organizational culture, Encar.com will raise the standards of used car transactions by one level and present a new benchmark for transactions in the used car market.”

IT Donga reporter Kim Dong-jin (kdj@itdonga.com)

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