June 14, “AI Symbiosis & Resilient Growth — Data Story Smart Mobility Industry Growth Forum” was successfully held in Chongqing. The forum gathered industry research institutions, university experts, platform representatives, ecosystem partners, and automotive industry partners to conduct in-depth exchanges on topics such as the development situation of the “15th Five-Year Plan” automotive industry, AI-driven GTM full-link upgrades, Chinese automotive brand globalization mindset construction, brand GEO strategy, AI marketing implementation, and platform growth closed loops.
In Chongqing, an important automotive industrial base, Data Story and industry partners discussed together: In the new cycle of deep integration of AI and mobility, how can car companies transform technical variables into deterministic growth capabilities and truly build resilient growth that transcends cycles.
In the opening speech of the forum, Liu Shihua, Director of Chongqing Municipal Financial Development Service Center emphasized: "Smart mobility is essentially a complex systematic engineering project with 'high investment, long cycle, and multiple entities'. It requires coordinated promotion of finance, technology, and industry to build a sustainable ecosystem. At the critical moment of industrial transformation and upgrade and intelligent globalization breakthrough in the automotive industry, finance is not only a tool for resource allocation with numbers, but also an important force to promote industrial resilient development. With digital technology penetrating the transportation industry comprehensively, finance is forming a more three-dimensional support network from payment system, infrastructure support to risk sharing mechanism."
And the meaning of this support ultimately points to a more realistic question: How to make a highly complex industrial system continue to operate in an uncertain environment. Wu Shouxi, Director of Industry Development Research Department, China Automotive Information Technology (Tianjin) Co., Ltd. brought “15th Five-Year Plan” Automotive Industry Development Situation and Analysis theme sharing, pointing out from three dimensions of global economy, domestic consumption, and industrial structure: The automotive industry has entered the "low-speed steady state + structural differentiation" stage from the high-speed growth stage, and the core of industry competition has shifted from "incremental contention" to "stock efficiency". Exports, intelligence, and new energy penetration rates are still core variables, but the overall market is entering a longer-term and more complex game cycle.
In his opinion, the automotive industry is entering "structural competition" from "scale competition", and enterprises need to shift from "short-term response" to "long-term capability construction".
01 GTM Intelligent Upgrade, Let AI Truly Enter Car Company Growth Link
"If you compare business competition to a marathon, what ran on the track in the past was 'people'. Enterprises invested a lot of digital construction in the past five to ten years, which was like building supply stations along the road to support employees to run faster and further. But today, the protagonist on the track has changed — what is truly running has become AI, while people have stepped back to become coaches setting directions from a higher dimension." Zhao Xiaodong, Vice President of Data Story mentioned in the theme speech "GTM Intelligent Upgrade Under AI-Driven Organizational Transformation". He pointed out that just as robots compressed half-marathon results from 2 hours 40 minutes to 50 minutes in a short year, the evolution speed of the business world has also been completely reset.
Under this irreversible trend, the organizational form of enterprises is undergoing a qualitative change. He emphasized a core strategic concept proposed by Data Story this year — Agent Enterprise, that is, an Enterprise Driven by AI Agents. In this new form, AI is no longer a software tool passively waiting for clicks, but has become a "new type of labor force" existing in the corporate address book. To support this transformation, enterprises need not only to build a "World Model" that fuses business objective data and organizational emotional culture as the decision-making brain, but also need to establish a management system to recruit, train, and even assess AI employees just like managing human resources, allowing AI to deeply participate in business processes and collaborative decision-making.
To truly complete such transformation, enterprises need to build three layers of capabilities:
The first is the Business Decision Layer, building the "Enterprise World Model", letting AI understand the enterprise's real business logic, shifting strategic decisions from experience-driven to data and model-driven, achieving AI participation in decision-making to form a closed loop.
The second is the AI Organization Layer, establishing an AI Agent and Digital Employee Management Platform, giving AI clear role definitions, training mechanisms, and collaboration relationships, managing AI like managing human resources, achieving "AI can be recruited, trained, and assessed".
The third is the Application Scenario Layer, embedding AI capabilities into the full process of marketing, sales, and services, forming a human-machine collaboration closed loop from content production to sales conversion.
Current automotive marketing has shifted from the past quarterly planning model relying on large media exposure and premium large-scale production to content competition that responds daily or even hourly. Users no longer simply enter the sales funnel preset by brands, but enter a "Content River" composed of search, social media, AI Q&A, and KOC content. In the environment of budget pressure, traffic fragmentation, and intensified competition, car companies must possess content scale, trust density, response speed, and data memory capabilities simultaneously.
After reconstructing organizational forms, how to break the dead knot of "tight budget, difficult conversion" for car companies? Zhao Xiaodong proposed an AI-driven KOX Brand Growth Operating System of "One Center, Two Approaches, Five Grasps" on site: Using AI-ified Center as the command system, using AI Agents to collaborate with real consumers, sales personnel, employee partners, cooperative ecosystems, and AI entrance touchpoints. One end completes brand planting, the other end takes on sales conversion, fully connecting the business closed loop from brand long-line "planting" to lead "conversion".
Entering the Agent Enterprise era, Data Story has taken the lead in practice, building the AI Business Decision Management Platform — EntVerse+Navi, structuring enterprise organization knowledge through Context Engineering, enabling AI to understand and call real business contexts. The automotive enterprises we serve can also rely on this platform to take the lead in building their exclusive "Enterprise-Level Commercial World Model", truly owning an "AI Brain" that understands mobility business and can go down to the ground to fight, effectively transforming technical variables into visible resilient growth.
02 Chinese Automotive Brand Globalization, From Market Entry to Mindset Entry
Chinese automotive brands are accelerating towards the global market, but true globalization is not just about selling products to overseas markets.
A more critical question is: Do overseas users understand the brand? Are they willing to trust the brand? Can the brand establish long-term mindset in different cultural contexts?
Around this core question, Lai Minru, Vice President of Data Story brought "AI-Empowered Construction of Dual Brand Mindset for Chinese Automotive Brand Globalization" theme sharing. And pointed out that Chinese automotive brands are entering the second stage of globalization — from product going global to brand going global, and the true next stage is "Mindset Going Global".
She mentioned that in the AI era, brand visibility is being redefined. Users no longer rely on search engines to get information, but get answers directly through AI. In this process, whether a brand is mentioned by AI and whether it is recommended by AI is becoming a new key indicator — AI Mindset.
In the AI Brand Mindset research conducted by Data Story in 11 countries, the brand AI mindset levels of different overseas markets show obvious differences. For example, in some Chinese automotive brands in markets like Thailand, Indonesia, the AI mindset performance is relatively good, but in more markets, the Share of Voice where Chinese brands are mentioned by AI remains low. Even if the brand has a certain volume, at the specific mindset positioning level, such as intelligent cockpit, local services, technology credibility dimensions, there is still a gap compared with traditional international brands.
◎ Data Source: 2026 China Automotive Companies Going Global 11 Countries GEO Status Analysis White Paper
Chinese Automotive Brand Going Global is not just about doing exposure, but also about doing well "Source of Trust Construction" in the AI era. Including optimizing official website structure to make brand information easier for AI to index; laying out media reviews, automotive vertical websites, KOL/KOC content, and UGC content to let the brand form more stable and credible expressions in the AI context.
On specific implementation, Data Story built three AI Partners around brand globalization:
AI SOL is used to build the Brand Bible, helping brands complete localization narratives and core asset deposition;
AI MAX is used for consumer mindset construction, covering marketing plans, influencer selection, content creation, ad traffic, and effect monitoring links;
AI ACE focuses on AI Mindset Construction, from keyword discovery, problem library construction, official website optimization, source monitoring to content execution, forming a complete closed loop.
From product going global to brand going global, and then to mindset going global, the globalization competition of Chinese automotive brands is shifting from "selling to overseas" to a new stage of "being understood and trusted by overseas users".
03 Data Story × Chongqing University Releases "Automotive & Two-Wheeler Industry GEO Strategy and Practice White Paper"
When users' way of acquiring information shifts from "searching answers" to "asking AI directly", brand mindset construction also welcomes new variables.
On site, Data Story jointly with Chongqing University released the "Automotive & Two-Wheeler Industry GEO Strategy and Practice White Paper", and Li Xiaoling, Professor of Chongqing University and National Young Talent released and deeply interpreted the report on site. The white paper integrates academic research and industry practice, revolves around GEO strategy importance, new challenges in automotive industry AI search, and GEO full-link monitoring and optimization system, providing systematic ideas for how automotive and two-wheeler brands are seen, understood, and recommended in the AI recommendation era.
Professor Li Xiaoling pointed out that AI Native Apps have entered a new stage of user stickiness and population structure expansion from early traffic sprint. Data shows that AI App overall reach scale reached 440 million in March, and per capita usage frequency and usage time are also continuously increasing, AI search has deeply penetrated into user living habits. Not just young people, senior groups and lower than tier-three sinking markets are also becoming new growth groups for AI search.
Compared to traditional search, the change brought by GEO is more direct. In the past, users told search engines "what I want to find"; now, AI recommendation engines help users get information, and even further influence the decision of "what I should buy". This also brings several pain points of brand marketing in the AI era: Brands might not be mentioned by AI, might prioritize mentioning competitors, or might be mentioned but misunderstood or misquoted. Whether the content released on official websites, news media, and social platforms can be seen, understood, and adopted by AI is becoming a new competitive variable.
Around this change, the white paper proposes the three-layer goal system of GEO:
"Source is cited by AI", letting brand content be seen by AI;
"Source is adopted by AI", letting brand content become trusted information prioritized when AI generates answers;
"Become AI Anchor", forming a stable recommendation position in specific car buying scenarios (such as family cars, commuting SUVs, intelligent cockpits, etc.)
How to influence consumer decisions through "AI"? In the background where AI recommendation mechanisms dominate user decisions, it further proposes an "Scientific Decision Attribution System" reconstructed by AI participation. Based on real consumption paths and brand data structures of the automotive industry, the model constructs the ASEV four-layer decision link, used to explain the complete process of users from "generating needs" to "finally choosing brands".
Users start from generating mobility needs, and sequentially experience four stages of demand trigger, plan screening, attribute assessment, and pre-purchase verification. The decision path shifts from "user autonomous search" to a dual mechanism of "AI first screening + user final confirmation": AI first generates candidate plans in the demand scenario, then compares and assesses based on brand and vehicle model attributes, and finally completes credibility verification through social media word-of-mouth and real experiences, thereby jointly deciding whether the brand enters the recommendation and purchase decision link.
This GEO full-link monitoring and optimization system is Data Story's accumulated commercial data and AI practical combat capabilities deeply integrated with Chongqing University's rigorous theoretical methods, jointly building the "Data × AI × Methodology" underlying engine. By connecting the closed loop of "Consumer Need Understanding, AI Mindset Insight, and Competitive Strategy Output", we will provide car companies with a GEO practical path that understands users, understands AI, and has measurable effects, truly escorting brand sustained growth in the Generative AI era.
04 AI Marketing Implementation into Daily Life, From Content Efficiency to Business Closed Loop
AI marketing is no longer staying at the conceptual level, but is entering the real work scenarios of the automotive industry.
Wang Xiaohua, General Manager of Automotive Industry at BlueFocus mentioned in the theme sharing "2026, AI Marketing Goes from Imagination to Daily Life" that 2026 is becoming a key node for AI to truly intervene in automotive industry marketing communication. On one hand, model capabilities, Token costs, Agent paradigms, multimodal capabilities, and enterprise-level deployment conditions are rapidly maturing; on the other hand, the automotive industry also faces pressure of budget tightening, talent density decline, and competition involution, forcing brands to complete marketing work in more efficient ways.
In his opinion, automotive marketing in the AI era is not just single-point tool efficiency improvement, but to form a set of "AI Business Nervous System". From new car launch information integration to multi-language, multi-time zone, multi-culture adaptation in global communication, to daily social media operations, AI can use knowledge center, content kitchen, workflow engine, channel distribution, and effect attribution to connect information and processes originally scattered between clients, agencies, influencers, and suppliers. AI is not to create more content, but to help brands reduce communication loss, letting content production, collaboration distribution, and effect deposition enter a more stable systematic operation.
In the background of explosive content growth, automotive marketing also needs to answer another more critical question: How to convert content into trackable, optimizable, and depositable business leads?
Around this question, Wang Sixun, Senior Expert of the Platform brought "Kuaishou Auto: AI-Driven Full-Link Growth Closed Loop" theme sharing, starting from manufacturer official accounts and dealer daily advertising scenarios, decomposing the application of AI in material production, advertising placement, private message reception, lead follow-up, and model optimization.
He mentioned that compared to e-commerce, retail, and other industries, the automotive industry short video material supply is relatively less, and production costs are higher, therefore the maturity of AIGC material capabilities first brings the improvement of content supply efficiency.
At the same time, digital human live streaming, live streaming highlights automatic clipping, AI private message reception, invalid lead automatic tagging and other capabilities are also letting automotive marketing move from "content sent out" to the stage of "leads caught, effects optimizable, experiences deposatable". For car companies, the core of future marketing is not just producing content faster, but letting content, traffic, private messages, leads, and conversions form a closed loop. Only when every touch can be tracked, every interaction can be accepted, and every conversion result can feedback models, AI marketing truly enters the growth system from efficiency tools.
05 AI Symbiosis · Resilient Growth, Data Story Continuously Assists Smart Mobility Industry Intelligent Upgrade
AI is changing the growth logic of the automotive industry. It is not just a tool to improve efficiency, nor just a local optimization of a certain link, but it is reconstructing the way enterprises understand markets, connect users, manage content, deposit mindset, and operate leads.
For smart mobility enterprises, true resilient growth comes from continuous perception, rapid response, and systematic conversion of uncertainty. The significance of AI symbiosis also lies in letting enterprises have stronger self-evolution capabilities in complex environments.
In the future, Data Story will continue to deeply cultivate the smart mobility industry, with social media data, industry Know-how, and AI capabilities as the base, around the real needs of automotive brands in insight, marketing, content, leads, and sales conversion, continuously creating more actionable, callable, and reusable intelligent growth capabilities.
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