After a decade of a digital transformation of the automobile industry from its introduction to its landing, it has now entered a systemically advanced deep-water zone, and the “road map” outlined in the latest policy has brought a new climate from research and development to consumption。
“it is now very efficient to use the phone app to order near maintenance or car washes, which are easy and fast to digitize, and rarely meet the problems of standing in line for hours.” mr. Wang said to journalists. There are not a few of the owners with whom he feels the same. “in post-market services such as car washing, maintenance, repair, replacement, etc., we seek to provide users with a better service experience by upgrading the whole range of numbers. Hu xiaodong, co-founder, president and executive director of the tread tiger cars, acknowledged the effectiveness of the set-up's intellectual services。
It is clear that digitization has become an important direction and an imperative for the development of the automobile sector. In recent days, the ministry of industry and communications, the ministry of education, the general directorate of market supervision and the national data agency have jointly issued the digital transformation implementation programme for the automotive industry (hereinafter referred to as the programme). “in contrast to similar policies in the past, the programme has deployed a focused system-wide mandate from the entire chain of research and development, production, supply chain, marketing and services in the automobile industry, identifying development goals that are far-reaching in accelerating the digitalization, networking and intellectual transformation of the automobile industry.” the deputy secretary-general of the chinese association for automotive circulation considered this to be the case during an interview with the chinese automobile journalist。
Promoting accelerated transformation of industries
Today, the automobile industry is an important pillar of the national economy, in terms of its manufacturing, consumption and services. Its long industrial chain, its wide-ranging reach and its dynamic nature determine its focus area for the digital transformation of manufacturing。
“the digital transformation of the automobile industry is a necessary trend in response to the global technological revolution and industrial changes.” the member of the committee of experts of the chinese association of automobile circulation spoke of the profound transformation of the automobile industry over the past decade, from conceptual exploration to chain re-engineering. After the internet, big data, cloud computing, rapid development of artificial intelligence, and changes in consumer perceptions, consumer markets, especially during the transition from increased to stock competition in the automobile market, traditional management concepts, modes of production, marketing patterns and service patterns are beginning to “failure”, with companies, suppliers and distributors and service providers facing the option of keeping pace with digitalization, with greater room for development, or being eliminated. As a result, the digitalization of industries has become a common orientation. As a result, the programme proposes to increase the resilience and safety of the automotive chain by targeting high-quality growth in the automobile industry, focusing on smart manufacturing, and fully releasing data factor values。
“in a decade of digital transformation, car marketing has gradually moved from a traditional trading-oriented model to a new one centred on value operations.” this is an example of a shift that not only redefines the relationship between automobile firms and consumers, but even more opens up new growth spaces and profit paths. In the past, he said, traditional marketing methods had been relatively monolithic, making it difficult to reach the target customer with precision, while digital marketing had re-engineered the car capture link. Through the installation of full-source data mid-stations, automobile enterprises are able to integrate large-dimensional data, such as on-line, off-line, social media, and achieve user-precision images, thereby providing individualized marketing programmes tailored to the needs and preferences of different user groups. This precision marketing has significantly increased its responsiveness and effectiveness, as well as its conversion rate. In some cases, the use of marketing resources has increased by more than 30 per cent by digitizing clearly differentiated positioning and avoiding homogenous competition。
Lessons can be learned in order to take the path of digitalization of industries. “in the light of the policy trajectory of the last decade, the digitalization of the automobile industry has largely passed the three stages of strategic start-up, dedicated breakthroughs and systematization.” zhihong, director of the research centre for automotive innovation, north industrial university, stated that the period 2015-2020 could be seen as a strategic start-up phase, during which the strategic position and focus of the digital transformation of the automobile industry were defined. For the first time, china's manufacturing 2025, which was introduced in 2015, introduced the concept of “smart manufacturing” and placed the automobile sector as a priority area; the next generation of artificial intelligence development plans in 2017 and the 2019 circular on promoting the accelerated development of the industrial internet all refer to the digitalization of the automobile sector. In 2021-2024, the development plan for the new energy automobile industry (2021-2035), for the purpose of a dedicated breakthrough phase, explicitly set out “to facilitate the digital transformation”; in 2023, a level 3 and 4 auto-driving access explore was launched; and in 2023, a circular on further strengthening the management of the access, recall and online upgrading of the software of the smart net automobile products further refined the regulatory requirements for digital applications, such as the upgrading of the ota, security regulation, etc. Since 2025, the programme has been in an institutionalized phase, marking a new phase from single points to full-scale concerted efforts to break down the deep digitalization of the automobile industry, promote the transformation of the entire industrial chain, build sustainable ecosystems。
To date, the digitalization of the automobile industry has yielded some results. At the r & d level, digital means have significantly improved efficiency. For example, in auto-pilot computer simulation tests, the intensive intensive learning network (d2rl) achieves an efficiency increase of about 2,000 times directly in dual and tri-lane scenarios. Under the same criteria, traditional testing methods require tens of millions of tests, while the help of digital technologies requires tens of thousands. At the production level, the first car companies now basically build intelligent chemical plants and digital workshops, which not only increase manufacturing efficiency, but also improve quality consistency and flexible manufacturing capacity. In the post-market service chain, the standardization of services through digitization has effectively reduced industry grey space。
“it is clear that the progress and effectiveness of digitalization in the automobile industry has been recognized by all sides, and that digital intellectualization is the new phase of digital leaps.” according to hiro hong, over the years, the digitalization of the automobile industry has a certain data “assets” base, and digital intellectualization has enabled full exploitation of data values. Digital intellectualization is by no means a simple addition of “digitized + intelligentization”, but rather a qualitative transformation and upgrading of “1+1>2” through technological integration. As the industry accelerates its transition to digital intellectualization, it will drive the industry towards full-chain connectivity of data elements, the penetration of intelligent landscapes, the evolution of industrial eco-synergy, providing solid support for the high-quality development of the industry and the construction of a modern system of high-end, intelligent and green automobile industries。
Breaking the foundations of the puzzle and seeking value fission
Industry is generally of the view that the programme's six actions and 15 priorities are of great value as guidance for deepening policy implementation, promoting the digital transformation of the automobile industry and defusing the real challenges of the industry。
“the programme, as an enforceable measure, goes hand in hand with top-level design and related policies.” as stated in the ccp proposal for the preparation of the fifteenth five-year plan for national economic and social development, the promotion of technological upgrading and the promotion of the intellectual transformation of manufacturing sectors; and the introduction last year of the programme of work for steady growth in the automotive industry (2025-2026), which advanced the in-depth application of artificial intelligence technology and led to the digital adaptation of the industrial chain supply chain. The new intent of the programme is to introduce, for the first time, a digital transition system covering research, production, supply, marketing and life-cycle, a “chain-wide penetrating” design that breaks the fragmentation limits of previous policies and establishes a path to the transformation of stereoization in depth. Second, for the first time, the “value of release data elements” was identified as a core objective, distinct from the industry transformation path that had been dominated by hardware and equipment transformation. It proposes to achieve “unvisible availability” of data through block chain technology and to decipher long-standing data isolation challenges. At the same time, the strengthening of ai's application at key points, such as quality testing, supply chain optimization and marketing model innovation, marks a qualitative leap in the transformation of industry from “information tool applications” to “data intelligence-driven”. Third, in response to the distress of the weak digital base of smes, the innovative introduction of a “three-tier gradient” strategy promotes deep linkages between large and medium-sized enterprises in areas such as r & d design, production synergies, quality control and the construction of a digital ecosystem of “strong chains”。
It is clear from the programme that by 2027, digital technology will have been integrated in enterprise research, production, supply, marketing and in-depth assembly applications, leading to a significant improvement in enterprise's intellectual manufacturing maturity, productivity, etc., and a gradual improvement in the industry's supply and public service systems; by 2030, the overall quantitative intellectual development of the industry will have reached a high level。
“this reflects the strategic tempo of the programme to promote short-term infrastructure and long-term dynamism in the transformation of the automobile industry.” the short-term target proposed for 2027 could, in the view of the grand view, be considered a precise and quantitative “turn-down” period, which would result in a new breakthrough in r & d efficiency through the promotion of technologies such as cloud-based collaborative research and development platforms, virtual simulation tests, and a “shorter delivery cycle” that would rely on digitalization of the supply chain to address the challenge of power allocation in order to fluctuate through intelligent discharge systems and logistics data. The short-term goal is essentially to set a “digitized infrastructure compliance line” for the industry to build on the bottom line of technology applications and efficiency improvements. The long-term goal for 2030 is a “value fission period” for ecological synergy. Compared to short-term “hard indicators”, long-term objectives focus more on “soft power”, where “deep integration” means that digital intellectualization is no longer limited to technology applications but permeates business model re-engineering, such as individualized service recommendations based on user-driven data, and paints a blueprint for industry to leapfrog to “data-driven”. The digitalization of the industries identified in the programme, compared to previous policies, has resulted in an upgrading in dimensions, deepening of the hierarchy, international alignment, etc。
“the programme sets out 15 priorities, which are highly relevant to the challenges of breaking the reality in the industry.” in an interview with the chinese automotive news, zhejiang gang, co-founder and director of zhejiang wan gin, chairman of the zhejiang gang motor dealer group, stated that, in the past, stock backlogs, customer losses, sales and financial sector data had not matched the real pain of distributors. As the market became increasingly competitive, the traditional model of dealer management had become difficult to adapt to the new market competition environment and, as called for in the programme, full-scale efficiency gains could be achieved by moving forward with digital transformation and re-engineering of the management model through digital means. As in the inventory management chain, a digital system that analyses historical sales data, seasonal factors, regional market characteristics through smart algorithms and establishes accurate demand forecasting models that have reduced inventory turnover from 50 to 25 days and released significant liquidity。
“digitalization, as directed by the programme, is an important guide to defusing the real challenges of the industry, as the programme's priority, namely, the `diagnostic assessment and improvement of upgrading actions', can provide a `protocol' for defusing the difficulties associated with distributors.” it was also mentioned that distributors could use their own bottlenecks to conduct targeted assessments and upgrades in a digital manner, build data-driven precision marketing and avoid waste of resources from blind promotion under traditional models. Providing products and services tailored to their needs through precision targeting target user groups not only enhances marketing effectiveness but also enhances the identity and loyalty of users to the brand. In addition, in response to core challenges such as the non-transparent and inaccurate valuation of second-hand car transactions, a data network has been built to build solid data foundations for accurate valuation. On this basis, variables such as market supply and demand, regional differences, and new car prices could be incorporated into the digital system, and standardized and intelligent assessment systems could be established to address the root causes of congestion in used car transactions。
The mind-blowing scene opens up the imagination of the industry
It is worth noting that the programme has five links from auto research, production, supply, sale and clothing, where intelligent synergetic research and development, model-based system engineering, flexible and agile production, digital twin factories, supply chain intelligence synergy, data-driven marketing, active user services, data value-added services, and eight digital intellectual scenarios。
“the introduction of a model scenario guide for the intellectual transition is a key feature of the programme.” from the perspective of kim, the typical scenario of digital intellectualization opens the way for business and provides a viable path to transformation. Entering the age of intellectualization, whether car research and development, manufacturing or marketing, services, requires data access and system integration and mobility. In a car business, intellectualization not only covers r & d, production, marketing, after-sales, user feedback and even complaints are incorporated into the data system, which allows the r & d sector to see user needs and analyse data, and the systematic upgrading of this intellectuality makes it easier for upstream and downstream enterprises to work together and around the market. At the same time, digital twinning plants have now been built in many cars, with flexible production lines on line, and digital intellectual systems have become an important basis for them. Data in this system can reflect both real market demand and extended services such as individual customization. As a result, the typical scenario presented in the programme is not remote, is being visualized and is an important trend in industry and enterprise transformation。
“data-driven marketing, proactive user services, as proposed by the programme, reflect important areas where the current industry is in dire need of transformation.” the grand view is that entering the age of digitization, networking, intellectualization, the needs of mainstream consumer groups are more diversified and individualized, and traditional marketing and service models have become difficult to meet consumer expectations. It is only through an in-depth analysis of user behaviour data and the construction of accurate portraits that individualized marketing and personalized services can be achieved, thereby highlighting features in intense market competition and fostering new profit growth points。
Hu xiaodong is more aware and aware of this. He described the fact that, in recent years, a complete digital system had been built up for the road tigers, covering the supply chain, door shop management, worksheet execution, customer interaction, and so on, resulting in the digitization of the entire post-car market and the intelligent operation. The first fully automated storage system in the industry was also launched in the land rover in 2025, which resulted in a 2. 5-fold increase in the efficiency of the storage, and in the pilot of undistributed distribution in nanjing, hangzhou, to explore new scenarios for “smart distribution + instant service”. In addition, the construction of an intelligent supply chain system is taking a step further, with the ai smart passenger service system of the tigers, increasing service satisfaction by 7 per cent and optimizing service experience。
At the same time, through an in-depth digital transformation, the tmvp has transformed the manual model, which previously relied on individual experience by repair technicians, into a quantifiable, replicable digital, standardized service system, while at the same time increasing the value of manual experience through technological empowerment and creating standardized service processes such as the tmvp eight-step process, which has reduced the reliance on the personal experience of the core technician by dismantling maintenance to 27 practical steps to achieve full process transparency and traceability。
“in the automotive sector, especially in the marketing and post-market areas, data value-added services have been identified as key players in breaking through homogenization competition and building differential advantages.” snowflake indicated that the nature of data value-added services is from functional provision to value cogeneration, i. E., service precision and personalization through the in-depth excavation of user behavioral data, vehicle running data and service interactive data. In the past, in traditional car marketing, more attention has been paid to the conclusion of single transactions than to the potential value of users throughout the vehicle purchase and use cycle. Through data tracking of the full cycle of user behaviour from car purchase to replacement, the implementation of a tiered operating strategy enables users to move from a one-time to a long-term value contributor, moving from a single transaction to a life-long connection。
Snowflake suggested that the digital value added of post-market services should also shift from reactive response to active empowerment. In the traditional service pattern, vehicles are not repaired until they fail, and such passive maintenance not only causes inconvenience to users, but may also cause safety risks. This situation is gradually changing based on predictive maintenance services based on vehicle-borne sensor data and cloud algorithm models. Automobile service providers are able to proactively send appointments such as testing and maintenance services to users through data analysis. This predictive maintenance model, which “prevents better than maintenance”, reduces the risk of vehicle failure and greatly enhances the user's sense of security and satisfaction with the use of vehicles, as well as the service provider's ability to secure stable customers and profits. In addition, companies and dealers working with users on the basis of compliance, mutual trust and exploitation of the value of vehicle-borne data and the provision of cross-border services have also become one of the avenues for the exploration of digital value-added services that can provide new profit growth points for enterprises。
“when data value-added services enter the mature stage, they will present significant features of service digitization and data servicing.” according to hong kong, not only will data become an important asset for car companies and dealers, but it will also provide an important support for changes in car marketing patterns and service models. She stressed that the new year of the automobile industry, driven by the programme, would usher in a period of good opportunity for intellectual transformation, which would help the industry truly to achieve a user-centred re-engineering of values, accelerate the move of the automobile industry from the traditional “product-driven” “service-driven” to the “value-driven” of the digital intellectual age, and build a new pattern of car industry development。
