AI accelerates its entry, on the eve of the explosion of the global automotive aftermarket

When a 2014 Buick LaCrosse failed to start due to a wiring fault, and the car owner independently completed vehicle diagnosis and repair with the guidance of the built - in AI using a $79 device, a story of industrial transformation driven by AI technology is quietly unfolding in the global trillion - dollar automotive aftermarket.

The automotive aftermarket generally refers to all services and transactions generated around the vehicle's usage lifecycle after it is sold. From maintenance and repair to parts replacement, it constitutes a large and complex ecosystem.

However, in this vast ecosystem, the digitalization process of automotive diagnosis, which is a crucial part for accurately locating faults, has been extremely slow.

The AI wave is sweeping across the global consumer sector, but automotive diagnosis is still blocked by high costs, complex protocols, and high - walled barriers of professional knowledge. Why is it so difficult for the tentacles of AI to truly shake the solid professional barriers in repair shops?

This industrial contradiction has become the breeding ground for a new generation of game - changers. TOPDON, a Chinese domestic brand, is one of the emerging intelligent hardware manufacturers. With "software - defined hardware + AI - reengineered processes" at its core, it acts as an "industry rule - redefiner", sinking and reconfiguring industrial - grade diagnostic capabilities to the consumer level through technological innovation.

Market performance has proven its success. In the automotive repair tool category on Amazon, its products have consistently ranked high on the best - selling list. Through in - depth educational content on platforms such as YouTube and TikTok, it has achieved efficient conversion from user awareness to purchase decisions.

Category Innovation:

Carving out a "New World" from the Industrial Red Ocean

According to Statista data, in 2024, the global automotive aftermarket scale exceeded $1.9 trillion. It is expected that the market will continue to grow in the next few years, reaching approximately $3.3 trillion by 2033.

(Estimated global automotive aftermarket scale in 2024, source: Statista official website)

Currently, the global traditional automotive diagnostic market presents a pyramid structure: at the top are the original equipment (also known as OE equipment) used by 4S stores; in the middle are the industrial - grade comprehensive diagnostic equipment used by professional repair shops (such as TOPDON's Phoenix series); at the bottom are the simple consumer - grade tools with a focus on functionality used by DIYers/ car owners.

TOPDON is targeting the "professional consumer - grade" segment that has been long - neglected but has great potential.

"This is a typical'middle gap' market," analyzed Lou Ke, the chairman of Dingjiang Innovation Technology Co., Ltd., in an interview. "Professional equipment is too expensive and complex, while simple tools lack functionality. However, the demand is real - more than 30% of the 80 million car owners in the United States have tried DIY repairs, and the proportion in Europe is 25%."

How big is this market? Lou Ke did some calculations: there are 80 million car - owning families in the United States, 120 million private cars in Europe, and 300 million car owners in China. If 10% of them are willing to buy diagnostic equipment, it will be a market worth hundreds of billions.

"More importantly," Lou Ke analyzed, "with the relaxation of mandatory vehicle scrapping policies and the increase in vehicle usage years, as cars age, this demand will grow. The older the car, the more faults it has, and the stronger the diagnostic demand."

"Just as DJI turned drones into 'flying cameras', we aim to transform automotive diagnosis from a professional tool into a consumer product," Lou Ke defined the company's mission.

In October 2023, TOPDON launched the $79 TopScan device on Amazon. There were already many players in this category at that time, with monthly sales generally ranging from two to three thousand units. However, TOPDON's product disrupted the balance as soon as it was launched. "We sold over 10,000 units in a single event and over 100,000 units in a year," 36Kr learned. Currently, the global user base of the TopScan and Carpal series has exceeded 430,000.

(TopScan - DIY automotive diagnostic tool/ source: the enterprise)

How did this best - selling product come about? Lou Ke simply explained the reason: "The $79 product achieves 90% of the functions of the original equipment, which costs three to five thousand dollars."

Based on the experience of the best - selling product, TOPDON launched a three - tier product matrix: the Carpal series for entry - level novice car owners, the TopScan series for professional technicians, and the Phoenix series for repair shops.

A successful category creation requires a set of differentiated implementation paths. TOPDON has built an iron triangle of "localized product definition + global supply chain + regional content marketing".

The key to achieving "professional yet user - friendly" lies in TOPDON's unique "Lego - style" architecture - modularizing complex diagnostic functions, allowing users to combine and call them as needed, presenting industrial - grade capabilities with a consumer - grade experience. In contrast, traditional industrial equipment has fixed functions and is difficult to disassemble.

Meanwhile, establishing professional trust has become another core barrier. TOPDON has adopted a "professional outreach" strategy: in addition to content platforms such as TikTok and YouTube, it has also deeply cooperated with automotive media, industry associations, racing events, and training schools. It conveys the brand's warmth through certification endorsements and real - user stories, rather than simply selling products.

As of 2025, TOPDON has sold its automotive diagnostic tools and other products to 140 countries around the world. In that year, the company's overall annual revenue was close to $300 million, with the North American market being its core pillar, contributing up to 65% of the revenue.

"Currently, 65% of our revenue comes from diagnostics, 18% from thermal imaging, and 17% from battery solutions. In the battery testing category in the United States, our market share is close to 40%," Lou Ke revealed.

(TOPDON diagnostic product series/ source: the enterprise)

AI Upgrade:

Becoming the "Second Brain" of Automotive Diagnosis

Currently, the competition in the automotive diagnostic market mostly stays at three superficial levels: competing in hardware parameters, covering more vehicle models, and having faster data updates.

In Lou Ke's view, this is essentially a primary competition of "data porters". "Traditional tools only present information, while the real value lies in decision - making support."

After seeing the essence of the industry competition, TOPDON has built its own unique competitive moat - the key still lies in software, and hardware is just the carrier.

Lou Ke revealed that TOPDON spent five years and hundreds of millions of dollars building a underlying technical architecture that is on par with industrial giants. Its self - developed communication protocol can cover 151 passenger car brands and 105 motorcycle brands globally, totaling over 20,000 vehicle models, achieving true global vehicle model compatibility.

What's more noteworthy is its design concept of hardware serving software. 36Kr learned that TOPDON's "Lego - style" modular hardware architecture allows different models of devices to share core modules, achieving functional differentiation through software configuration.

The direct advantage of this architecture is cost control and rapid iteration. "The same hardware platform can support new vehicle models and functions through software upgrades," Lou Ke said. "This makes our R & D efficiency more than three times higher than that of traditional manufacturers."

In addition, in 2025, TOPDON officially launched its self - developed AI diagnostic platform (TopFix), marking the company's strategic leap from a "smart hardware" company to an AI - driven "diagnostic solution" provider. Core businesses such as automotive diagnosis and infrared imaging have thus been empowered by AI, entering a second growth curve of scale and intelligence.

(TopFix AI/ source: TOPDON official website)

"With the arrival of AI, the repair process will be interactive," Lou Ke described the future scenario. "Scan the vehicle, and AI will tell you if there are any faults, whether it can be driven, whether it needs to be repaired, how to repair it, what parts are needed, where to buy them, how to replace them, and whom to ask for help."

What TopFix AI aims to do is like a general practitioner. It not only knows the symptoms but also can diagnose the root cause, prescribe treatment, write instructions, and find the right expert.

Compared with traditional automotive diagnosis, the first is the reconstruction of the diagnostic path. Traditional diagnosis relies on technicians' experience, following a "human - looking - for - problems" model; while AI diagnosis follows a "problems - finding - humans" model.

Through machine learning of a large number of repair cases, TopFix AI can establish an intelligent mapping from symptoms to root causes. TopFix can not only identify faults in sensors but also conduct cross - level causal inferences through data flow analysis and circuit knowledge bases, which is difficult for traditional tools to achieve.

(TopFix interactive repair process/ source: the enterprise)

Secondly, it is the reconstruction of the knowledge transfer method. The high threshold of professional - grade equipment is not only due to the high - cost hardware but also because it requires in - depth professional knowledge for operation. Through interactive guidance, TopFix AI "packages" professional knowledge into a portable and communicative operation process. "In the future, even without manual operation, voice commands can complete the processes of diagnosing, inspecting, and repairing vehicle faults," Lou Ke described. This enables industrial - grade capabilities to truly "sink" to consumer - grade users.

A deeper - level reconstruction lies in the business model. TOPDON is shifting from "one - time hardware sales" to a SaaS model of "hardware for customer acquisition + continuous profit from software services". Its software revenue is expected to grow from tens of millions in 2025 to $200 million in 2027.

The underlying logic of this growth stems from an ever - strengthening flywheel effect.

As the sales volume of the equipment increases, a large amount of diagnostic data continuously nourishes the AI model, making it more accurate; and a more intelligent AI can attract more users. At the same time, the platform systematizes and productizes the professional knowledge traditionally scattered in technicians' experience and monetizes it through subscription services. Basic diagnosis has become an entry point, from which value - added services such as remote expert support and accurate parts recommendation are extended, continuously opening up new revenue streams.

High - quality diagnostic data will be the scarcest asset in the future automotive aftermarket. "The large number of real repair cases we have accumulated will be the best 'nutrients' for AI," Lou Ke emphasized.

In the AI era, the data assets in automotive diagnosis directly determine the accuracy of future products and their commercial potential.

Ecosystem Blueprint:

Advancing from "Smart Tools" to a "Diagnostic Ecosystem"

During the interview, Lou Ke told 36Kr that the company is not only facing technological challenges but also opportunities to reshape the industrial value chain.

Traditional diagnosis is just the first step. The real value lies in building a digital ecosystem that connects car owners, technicians, parts suppliers, and insurance companies.

This is also the reason why TOPDON decided to "go all - in on AI". The ambition of TopFix AI is not just a smart function; it is positioned as a strategic platform to redefine the industry's value distribution.

Currently, TopFix AI has achieved a qualitative change in diagnostic efficiency. A typical case vividly demonstrates this transformation:

A Buick car owner in the United States was at a loss when facing the "P0113" fault code, and traditional methods failed to solve the problem in several days. With the intelligent guidance of TopFix AI, a wire bitten by a mouse in the engine compartment wiring harness was finally found - the entire diagnostic process changed from blind trial - and - error to precise positioning.

"Traditional diagnosis relies on the experience accumulation of technicians. It takes a top - notch technician ten years to master the ability to judge complex faults," Lou Ke analyzed. "Our AI, through machine learning of millions of repair cases, has standardized and intelligentized the diagnostic path."

The efficiency improvement brought about by this transformation is astonishing. Data shows that after using TopFix AI, the average diagnostic time has been reduced from 2 hours in the traditional model to 20 minutes, and the first - time repair rate has increased from 65% to 92%.

In addition, TOPDON is building a more imaginative industrial cooperation network.

The parts ecosystem extending upstream has become the first breakthrough point. When the AI diagnosis detects a generator fault, the system can not only accurately locate the problem but also intelligently recommend the most suitable parts solution based on vehicle model, usage years, and repair history data.

What's more anticipated is the construction of a remote expert network. "Imagine that a repair shop in a small town in the United States can connect with a BMW expert in Munich at any time," Lou Ke described this scenario. "Through AR technology, the expert can 'see' the on - site situation and guide complex repairs in real - time. We plan to pilot this service in the United States in the third quarter of this year."

(ONE - TOPDON's new professional - grade diagnostic product in 2026)

The release of data value has also opened up a third growth curve. Under strict compliance, anonymized diagnostic data is becoming the industry's infrastructure. The vehicle's health data is of great value to manufacturers for improving design and to insurance companies for accurate pricing.

The concept with the potential for disruptive change comes from the third - layer layout - vehicle health management. "The current model is to repair the car after it breaks down. The future model will be predictive maintenance," Lou Ke described a new scenario. "By connecting the device to the vehicle for a long time, AI can give a 30 - day early warning of battery degradation, detect