German consumers are also starting to ask AI how to choose their next car; AutoScout24, Europe's largest online car trading platform, is also using AI for on-site vehicle search. When consumer demand is first filtered through AI systems, automakers need to know: has their model made it onto the AI recommendation list, and where does it rank?

On September 10, AutoScout24 and its leasing platform LeasingMarkt.de released a consumer survey: among 2,000 licensed respondents aged 18 to 65, 12.9% listed AI as an information source before their next car purchase or lease. Four days later, AutoScout24 announced an update to its vehicle search, stating that the new AI-supported search brought about 7.5% more inquiry intentions in German tests.

On one side, consumers are starting to use AI to research cars; on the other, trading platforms are using AI to help consumers find specific vehicles. AI applications in the automotive industry have entered the car selection process.

-01- Where Do German Consumers Get Information Before Buying a Car?

The survey conducted by Civey on behalf of AutoScout24 lists the information sources consumers use before their next car purchase or lease:

Information Source	Percentage of Respondents Mentioning It
Local dealers	47.4%
Comparison platforms	37.2%
Family and friends	28.3%
Online car trading platforms	27.8%
Automaker official websites	27.2%
AI	12.9%
Car magazines	9.4%

Local dealers still rank first, but AI has become a channel through which some consumers obtain car-buying information. Among respondents aged 30 to 39, the proportion using AI to research their next car reached 18.0%, higher than the overall sample's 12.9%.

This echoes the U.S. car-buying trend we discussed yesterday: some consumers, before contacting dealers, have already used AI to learn about models and powertrain options, and they continue shopping with a preliminary shortlist.

-02- What Conditions Do German Consumers Value Most When Choosing a Car?

The same survey also asked what consumers value most when choosing their next car.

43.7% mentioned purchase price or monthly payments; 41.2% mentioned daily running costs; 32.1% mentioned safety.

Powertrain preferences also differ significantly by purchase method: among those leaning toward leasing, 72.1% considered EVs or hybrids; among those leaning toward buying used cars, 58.3% chose gasoline vehicles.

These decision factors that consumers value most are the basic elements AI considers when recommending models.

For example, an office worker living in an apartment without a fixed charging station, commuting alone on weekdays and often driving out on weekends, might ask AI with requirements covering monthly payments, running costs, charging, and long-distance driving all at once.

Automakers need to make model information clear enough so that the system has a basis to include suitable cars in the candidate range, and your brand has a much greater chance of being recommended in a top position.

-03- Where Are Chinese Brands on Germany's AI Recommendation Lists?

AutoScout24's data reflects vehicle searches within its trading platform. IPSmoto observes another scenario: when consumers ask AI large models what car to buy, which models are included in AI answers, and where they are placed.

IPSmoto's August 2026 Germany "EV + Sedan" monitoring ranking shows the performance of leading models and Chinese brand models as follows:

Table 1: IPSmoto Germany "EV + Sedan" IPS Ranking (Partial), August 2026

Rank	Model	IPS (Intelligent Promotion Score)	VS (Visibility Score)	RS (Recommendation Score)
1	Tesla Model 3	66.3	73.7	58.9
2	Hyundai IONIQ 6	42.5	53.5	31.5
3	Mercedes A-Class	36.8	42.5	31.1
4	BMW i4	34.8	43.4	26.2
5	Volkswagen ID.7	33.8	41.8	25.9
11	BYD Seal	9.6	14.8	4.3
24	NIO ET5	0.8	1.4	0.2
26	XPeng P7+	0.7	1.2	0.1
28	MG IM5	0.6	0.8	0.3
40	MG MG4	0.2	0.3	0.1

*Source: IPSmoto, August 2026 Germany "EV + Sedan" monitoring results, covering five mainstream large models: ChatGPT, Gemini, Claude, Grok, and Perplexity. IPS, VS, and RS are three indicators in IPSmoto's monitoring system, reflecting a model's overall recommendation performance, visibility, and recommendation strength, respectively.

In terms of ranking structure, Tesla Model 3 stands alone in the first tier with an IPS value of 66.3, about 1.6 times that of the second-place Hyundai IONIQ 6 (42.5); eight battery electric sedans from Mercedes, BMW, Volkswagen, and Audi occupy positions 3 to 10, and German domestic brands still retain a group advantage in the mid-to-high-end segment.

Among Chinese brands, the highest-ranked is the BYD Seal at No. 11 (IPS 9.6), just one step away from No. 10 Mercedes EQS (10.3); NIO ET5, XPeng P7+, MG IM5, and MG4 also entered the top 50.

Overall, Chinese brand models have entered AI's recommendation field of view in Germany, but there is still a clear gap with the leaders in both visibility (VS) and recommendation strength (RS): for example, the NIO ET5's IPS value is about 1.2% of the Model 3's.

This table presents the recommendation performance of AI large models under specific monitoring conditions, not a German car sales ranking. It shows that Chinese brand models have entered Germany's AI recommendation lists, but still have a clear gap with the top brands.

For automakers entering the German market, simply knowing they are "on the list" is not enough. What matters more is: under what car-buying questions is the model mentioned? In what position does it appear in AI answers? What sources does AI cite? These questions relate respectively to brand visibility, recommendation position, and the content sources supporting the recommendation.

-04- Which German Media Are Influential?

Behind every recommendation list AI provides are specific sources. Consumers see the answer, but automakers must ask where AI's answer comes from and whom the large models cited.

IPSmoto compiled statistics on cited sources under the same monitoring conditions. In August 2026, in monitoring scenarios related to "EV + Sedan" in the German market, the media most cited by large models were as follows:

Table 2: IPSmoto Germany "EV + Sedan" Media Citation Ranking (Partial), August 2026

Rank	Model	IPS AI Recommendation Index	VS Visibility Score	RS Recommendation Score
1	ADAC	adac.de	1490	60
2	MeinAuto	meinauto.de	1396	40
3	InsideEVs Deutschland	insideevs.de	1300	21
4	FINN	finn.com	1221	14
5	Elektroquatsch	elektroquatsch.de	647	8
6	mobile.de	mobile.de	478	16
7	Vogel	vogel.de	270	2
8	YouTube	youtube.com	254	57
9	Auto Bild	autobild.de	227	32
10	Beev	beev.co	209	5
14	Reddit	Reddit.com	177	52

*Source: IPSmoto, August 2026 Germany "EV + Sedan" media citation monitoring. The citation index and number of cited articles are calculated based on answers from each mainstream large model during the monitoring period.

The ranking shows a clear hierarchy of sources. At the top is ADAC—with a citation index of 1490 and 60 cited articles. The tests and reviews by this German automobile club have almost become a basic reference for large models judging models in the German market.

The second layer consists of vertical EV media and trading platforms: InsideEVs Deutschland, FINN, Elektroquatsch, mobile.de, etc., which form the main corpus for AI answers to EV questions.

The third layer is traditional automotive media: Auto Bild ranks No. 9 with a citation index of 227, while auto motor und sport ranks only No. 42. Notably, YouTube and Reddit also entered the top 15; community discussions and video content are being systematically cited by AI.

Beyond media, brand official websites are another key source. IPSmoto's official website citation monitoring shows that in August, among answers to Germany EV sedan-related questions, the brand official websites most cited by AI were as follows:

Hyundai IONIQ's official website ranked first with a citation index of 377 and 16 cited articles;

NIO Firefly (nio.com) ranked second with 186;

BYD Sea Lion (byd.com) ranked third with 51;

Lucid and Mercedes official websites ranked fourth and fifth, respectively.

In other words, when consumers ask AI about specific models, large models will go directly back to brand official websites' model pages to find answers—whether the official website can be "read" by AI is now affecting whether a model can enter the recommendation list.

Among Chinese brands, the German-language official website content of NIO and BYD has entered AI's citation system, which is a starting point well worth noting.

For Chinese automakers entering the German market, these data point to three specific tasks:

First, enter authoritative evaluation systems. ADAC tests and Euro NCAP ratings (citation index 51, ranking No. 44) are important bases for AI to judge models. Without these third-party evaluations, it is harder for brands to gain credible endorsement in AI answers.

Second, manage vertical media and platform content in the German-speaking market. EV vertical media, car trading platforms, videos, and community discussions together influence what model information AI can retrieve and how it understands a car's advantages and suitable use cases.

Third, build brand official websites into authoritative sources that AI can read. The clearer, more complete, and more locally contextualized the model, configuration, price, charging, after-sales, and applicable conditions are, the easier it is for AI to cite them accurately and the more basis it has to include the model in the recommendation list.

Dealers remain the most commonly used car-buying information source for German consumers, but the decision path before consumers reach a dealer is changing: they are starting to use AI to research vehicles, and car trading platforms are also using AI to improve car-finding efficiency. AI will not replace dealers or automotive media, but it is becoming a pre-filter in the car-buying process.

This means that automakers' marketing work needs to extend one step forward. In addition to tracking sales, search rankings, and dealership inquiries, they must continuously measure whether their models appear in AI answers, in what position, alongside which models they are compared, and what sources AI relies on to make recommendations.

This is precisely the new link that IPSmoto hopes to help automakers see clearly. IPSmoto covers five mainstream large models—ChatGPT, Gemini, Claude, Grok, and Perplexity—and can continuously track model visibility, recommendation position, and cited sources by market, powertrain type, and vehicle category, making the previously hard-to-observe AI car selection process measurable, comparable, and easier to manage for marketing.

*Citation Sources

1. AutoScout24 and LeasingMarkt.de consumer survey: https://www.autoscout24.de/unternehmen/daten/so-tickt-deutschland-beim-naechsten-auto/
2. AutoScout24 AI vehicle search announcement: https://www.autoscout24.de/unternehmen/corporate-meldungen/autoscout24-startet-neue-ki-fahrzeugsuche/
3. IPSmoto Germany electric sedan IPS ranking and citation monitoring: https://www.ipsmoto.com/