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63% of U.S. car buyers use AI to choose cars, but 71% of dealers have not adjusted for AI search. The report reveals a key problem: 41% cannot tell whether AI is working. Marketers need to learn the “measurement” lesson, establish metrics such as IPS (Intelligent Promotion Score), and put AI recommendation performance into their dashboards to win growth in the new decision journey.

The first step after receiving an IPS report: Understand the causal chain from AI recommendations to user decisions, rather than just looking at the total score. Through the CISCAS full chain, from comprehensive scoring, VS/RS diagnosis, nine dimensions, competitive benchmarking, and audience differences, deconstruct layer by layer to identify the problem areas of the brand in the AI ecosystem, formulate priority strategies, and achieve precise optimization.

IPS helps automakers play dual roles: as a growth lever when attacking, and as a defense against AI hallucination risks when defending. By monitoring AI recommendation performance, verifying tech attributes, focusing on high-end dimensions, etc., it solves problems such as traditional automakers' "AI aphasia", insufficient cognitive density of new forces, and dilution of pricing power of luxury brands, ensuring that the brand's voice and health in the AI world are controllable.

IPS uses three verification layers (repeated queries, fixed prompts, and multi‑model cross‑checks) to deliver reliable data across 16 markets and leading LLMs. It helps automotive brands track AI‑driven brand perception in real time—from early‑stage prediction and competitor analysis to diagnostic insights, global market guidance, and KPI evolution—paving the way for the transition from legacy search to AI‑native marketing.

IPS (Intelligent Recommendation Score) vs. Traditional NPS: The New Benchmark for Brand Growth in the AI Era. IPS quantifies a brand's recommendation strength within AI engines, including visibility and priority scores. It is highly correlated with sales, enables preemptive market trend prediction, compensates for NPS's lagging nature, and helps CEOs make precise decisions.

AI is deeply embedded in the consumer car-buying decision chain: 88.6% of Chinese consumers use AI assistance before purchasing a car, and nearly half of global respondents use AI to compare vehicle specifications. The logic of brand competition is shifting from "people seeking information" to "AI providing answers," with vertical media sources cited at a rate as high as 77.2%. Automakers need to embrace AI as a source of information to secure a place on AI-generated car-buying shortlists.

IPS (Intelligent Recommendation Score) scientifically evaluates global brand health through category isolation, repeated validation (30 questions averaged), and a 14-question system, combined with dual indicators VS (Visibility) and RS (Priority), to quantify AI recommendation rankings across 16 countries in multilingual markets, diagnosing brand competitiveness upfront.

Chinese automakers are accelerating their global expansion, with exports potentially reaching 10 million units by 2026. However, they face a blank brand mindshare overseas and the restructuring of AI-driven decision-making. The IPS Intelligent Recommendation Index covers multilingual testing across 16 countries, pre-judging brand rankings and consumer preferences in overseas AI systems, with a sales fit R²>0.82. It helps automakers shift from 'channel distribution' to 'being seen by AI', achieving mindshare going global.

AI is becoming the core entry point for car purchases, with 88.6% of consumers using AI tools to choose cars. Traditional CSAT/NPS metrics focus on post-event feedback and cannot evaluate AI recommendation performance. IPS measures brand visibility and priority in AI engines, becoming a new North Star metric for automakers. Embrace IPS, deepen AI source cultivation, and drive sales growth.