Gasgoo Munich-In 2026, the auto industry's AI narrative is getting a rewrite.

If 2024 was the year of "large models in cars" and 2025 belonged to "end-to-end," 2026 is staking its claim on a single phrase: the unified agent. It's the buzzword at nearly every tech launch.

Yet in production vehicles, the old split persists: cabin AI handles interaction, while ADAS handles driving. Is the industry's push for a "unified agent" a technical reality closing in—or just a narrative that needs a reality check?

At the fourth AI-Defined Vehicle Forum, hosted by Gasgoo, a roundtable tackled the question: "Full-Domain AI: Are Cars Moving Toward a Unified Agent?" Panelists Gao Jie, NIO's head of cabin AI; Wang Haowei, global ADAS chief at JOYNEXT; and Ma Jian, vice president of sales at THESEUS, hashed out the details.

When the industry says "unified," what exactly is it unifying? How do the technologies merge? How is safety maintained, and what serves as the foundation? These questions surfaced again and again.

The Unified Agent: What, Exactly, Is Being Unified?

Before answering whether cars are evolving into unified agents, a prerequisite must be cleared up: what does "unified" actually mean in this context?

A look at the actual solutions hitting the road reveals that "unified" is far more complex than it sounds.

Image credit: Geely Auto Group

Geely’s Full-Domain AI 2.0 hinges on a "1+2+N" multi-agent framework. The vehicle-level agent Eva sits at the core, coordinating two primary domain agents—driving and cabin—alongside sub-domain agents for chassis, energy, and body control. The goal isn't one model to rule them all, but rather a system where agents across domains can talk, negotiate, and collaborate.

Volcano Engine takes a "single brain" approach. Its end-to-end AI cabin architecture uses a central AI brain to deeply link the entire vehicle, closing the loop from perception to reasoning, execution, memory, and learning. Yet Volcano Engine vice president Yang Liwei draws a pragmatic line: "Volcano Engine is more like the brain, while smart driving is the cerebellum handling motion control." The brain interprets user intent and hands it off to the cerebellum—it doesn't replace it.

Image credit: NIO

NIO, meanwhile, redefines the boundaries of "unification" from the ground up. Its in-house full-domain operating system, SkyOS·Tianshu, bridges six domains—smart assisted driving, cabin, chassis, body, power, and cloud—unlocking over 1,600 atomic capabilities. It unifies management and scheduling across all domains. The significance? Rather than slapping a unified interface onto the application layer, it4 pulls capabilities from separate domains into a single scheduling1 scheduling system at the OS level—giving the unified agent a foundation it can actually run on.

Gao Jie, Head of Cabin AI at NIO

During the roundtable, Gao weighed in on what a vehicle-wide agent should look like. As touchpoints get smarter, agent-based software will multiply—"an inevitable form, an objective fact," he argued. Still, the user-facing interaction layer needs a unified agent in charge. "Since NOMI's first day, we wanted it to be the car's soul—like a human brain, aware of everything," he said. His ideal form for a vehicle-wide agent: "centralized yet democratic." Sub-agents run autonomously, but the master brain knows all.

Despite differing approaches, the industry's trajectory is clear: unify the interaction portal, unify the semantics, and execute safely in a distributed manner. "Unified" doesn't mean one model replacing all subsystems. It means preserving domain autonomy while letting interaction, semantics, and data flow freely.

For users, whether one agent or many hums in the background hardly matters. Seamless experience and reliable safety are the real benchmarks. And seamlessness hinges on whether the cabin and driving systems can truly work in sync.

Cabin-Driving Integration: How Far Has It Come?

With the "unification" direction coming into focus, the technical path gets more concrete: what logic should drive cabin-driving integration, and how far along is it today?

The industry has floated several solutions to the merging puzzle.

One classic route centers on chips and hardware architecture, with Horizon Robotics leading the charge. Its Xingkong 6P chip, built on a 5nm automotive process, delivers 650 TOPS of BPU computing power and 273 GB/s of memory bandwidth. By unifying memory and base software, it shifts vehicle computing from isolated domain controllers to central computing—halving space usage, cutting per-car costs by 1,500 to 4,000 yuan, and shrinking R&D delivery from 18 months to 8. "Integration is the immutable law of computing systems," Horizon founder and CEO Yu Kai argued.

Image credit: Dongfeng Motor

On the automaker side, Dongfeng Motor and Black Sesame Technologies co-developed the Tianyuan Smart Cabin Plus platform. Powered by the Wudang C1296 chip, a single processor simultaneously supports the smart cabin, L2+ driving assist, and parking—debuting in the Dongfeng eπ007, with broader rollout across multiple production models planned for 2026 and 2027.

Volcano Engine opts to bridge the gap at the model layer, without forcing chip-level unification. Yang offered a key data point: driving models demand inference frequencies of 10 to 48 Hz, while cabin models need just 1 or 2 Hz per second for smooth interaction. "Different processing frequencies multiply the demand for underlying compute. There's no need to merge the two models right now—the cost-performance ratio is poor." Volcano Engine's strategy: "precisely distill and summarize the user's intent for the driver agent, then transmit it to the driving system, closing the loop."

JOYNEXT takes a middle path, integrating chips and software via a central computing platform. Its nCCU series, built on Qualcomm's latest premium platform, supports deep fusion of the cabin and driving domains.

Wang Haowei, Global ADAS Head at JOYNEXT

For Wang, the real hurdle isn't technology—it's divergent needs. "Carmakers prioritize different things for the cabin and driving, and their software iteration speeds differ." His solution: "seek common ground while reserving differences." Unifiable requirements go into a unified architecture; the rest run on separate stacks.

NIO attacks the problem from the vehicle OS level. Its in-house SkyOS·Tianshu—the industry's first full-domain OS built for AI—operates on a core logic: cabin-driving fusion shouldn't be "connected" at the application or model layer. It must be hardwired at the OS level.

SkyOS·Tianshu bridges six domains—assisted driving, cabin, chassis, body, power, and cloud—unlocking over 1,600 atomic capabilities for unified management and scheduling across all applications.

This OS-level scheduling mindset shapes Gao's view of the boundary between driving and cabin. He offered a stark warning on the trend of driving domains encroaching on cabin interaction: "Over the past few years, smart driving has tried to do VLA and handle human-machine interaction from the driving domain. I think this direction is completely wrong. I totally disagree." His logic: driving decisions require a fast loop with "zero tolerance for misjudged frames," while cabin interaction is slow and high-level. The two are fundamentally different paradigms.

Approaches vary, but all paths must confront an unavoidable question: as cabin and driving fuse further, where do we draw the safety boundaries?

Interaction Can Unify; Safety Must Isolate

The deeper the technical debate goes, the more urgent safety becomes.

As large models stretch from the cabin into driving decisions, risk bleeds from the experience layer into road safety. Will large models make cars smarter—or just harder to control?

A March 2026 crash drew stark attention to this risk. A Lynk & Co Z20 was cruising when the voice assistant misinterpreted a command and switched off the headlights; the car then slammed into a highway median. The failure wasn't a lack of model "intelligence." It was the lack of isolation—interaction-layer output reached a safety-critical actuator unchecked.

Image credit: Waymo

Waymo offers a clear reference point. Its Ojai Robotaxi integrates Google Gemini as an in-car assistant, but under strict constraints: Gemini cannot alter the route, nor can it control windows or seats.

Crucially, Gemini is explicitly barred from claiming driving capabilities. One AI drives; another serves the passenger—and their permissions stay isolated.

On the hardware side, Horizon Robotics pioneered a "castle" architecture for physical safety isolation in its Xingkong chips. The cabin and driving domains run independently; the driving domain hits ASIL-D, the highest safety level, and a cabin reboot won't disrupt driving functions.

From a practical standpoint, Gao cut straight to the point: "In the short term, models are models, and product code is product code. All hard safety rules must be hardcoded. Don't hand them to the model." Wang was equally blunt: "No matter how smart autonomous driving gets, safely getting people from A to B is always the first principle."

The industry's de facto approach: unify at the interaction layer, isolate at the safety layer.

That doesn't conflict with the unified-agent vision—it's a realistic choice under today's engineering constraints. Yet it raises a deeper question: if safety isolation is mandatory and model layering is reality, what engineering foundation can keep a unified agent running sustainably?

Chips Matter, But What’s Truly Scarce?

Answering that requires returning to the basics of full-domain AI. Chip compute is growing, and central computing architectures are moving from concept to production. But whether these form the true foundation of full-domain AI remains a matter of debate.

Gao offered a clear verdict: "The core foundation of full-domain AI is full perception and full execution, plus central/pre-control architecture, the SDV software stack, and a data closed loop. If agents don't learn, the whole thing collapses." Chips and unified compute platforms, he stressed, "are bonus items, not the basics."

This view is gaining ground in 2026. From EV startups to legacy automakers, several have shifted their investment focus from features to underlying engineering systems.

Wang viewed it through the lens of AI infrastructure. In a keynote at the same forum, he argued that "models define the upper limit, but infrastructure determines AI's future." Future competition, he suggested, won't hinge on model capability alone—it will hinge on who can build the infrastructure to support continuous AI training, deployment, iteration, and scaling.

Though aimed at the broader AI industry, the takeaway applies to autos: as the unified agent moves from concept to production, what keeps it running may not be the model itself, but the engineering system that trains, deploys, and iterates it.

Image credit: @Grace Tao Lin-Tesla

Tesla's Shanghai Lingang AI Training Center, now online, closes the loop from data collection and local storage to domestic training, in-car deployment, and continuous iteration. This lets FSD handle full-pipeline data processing and model iteration within China, accumulating over 3 billion km of local road data. NIO, since 2021, has built its own data-loop framework and swarm intelligence validation system, enabling automatic data filtering on the car, cloud training, and parameter feedback. Its training architecture has evolved into a three-layer framework: world models, supervised fine-tuning, and closed-loop reinforcement learning.

These investments all point one way: making data drive model iteration more efficiently. That dictates not just today's feature performance, but whether the foundation can sustain continuous evolution.

Overall, the foundation of full-domain AI is shifting from standalone hardware or models to the engineering systems that keep turning data into model iterations. By 2026, this consensus has crystallized: chips and central computing remain necessary infrastructure, but the competitive focus is moving from "tops benchmarking" to "who can weave compute, data, and toolchains into an engineering system that keeps AI evolving."

The true scarce commodity is no longer any single technology—it's the engineering capability to keep technology running.

Conclusion

Returning to the roundtable's opening question: are cars moving toward a unified agent?

Technically, the answer is yes. Hardware solutions for cabin-driving fusion are in production, model-level semantic bridging is underway, and data-loop engineering frameworks are taking shape. But getting from "done" to "done well" spans a long road of engineering maturity, cost constraints, and safety responsibilities.

As for timelines, the panelists varied in specifics but agreed on direction. Wang figures comfortable interaction is "two or three years away," but deep integration into every vehicle layer—a true unified agent—needs "5 to 7 years." Gao bets "a point where the industry feels 'AI-defined vehicles' is valid could emerge in about two years," but "five years or longer before it becomes inevitable."

Beyond the timelines, the real question isn't "how long," but whether the unified agent can sustainably balance safety, experience, and iteration. Technical paths can advance in phases; safety boundaries must hold firm.

Gasgoo Munich-GreaTech Substrates broke ground on an advanced packaging substrate project on September 29 at the Sino-Singapore Guangzhou Knowledge City, according to the "Guangzhou Huangpu Release" WeChat account. Once completed, the facility will expand GreaTech Substrates’s capacity for high-end packaging substrates and bolster the regional semiconductor supply chain.

Image Source: Guangzhou Huangpu Release (Li Jianfeng)

The first phase spans 312 mu, with a total floor area of approximately 360,000 square meters. Its focus is high-end Flip Chip Ball Grid Array (FCBGA) packaging substrates, which are essential for data centers, high-performance computing (HPC), and cloud computing. Production from the site is expected to significantly elevate GreaTech Substrates’s technical strength and scale in the high-end substrate arena.

Public records show GreaTech Substrates Packaging Substrate Co., Ltd. settled in Huangpu District in 2021, focusing on RF, FC-CSP, and FC-BGA substrates. It has since become a core supplier for several leading global packaging firms. This new project is viewed as a strategic move to scale up capacity for the AI computing era.

Huangpu District is now home to more than 150 integrated circuit firms, forming a complete ecosystem that covers chip design, wafer manufacturing, packaging and testing, equipment and components, and end-use applications. The district holds about one-tenth of the country’s PCB capacity. Between January and August 2026, the local semiconductor and integrated circuit sector generated over 31 billion CNY in output value—a 36.6% jump from the previous year. This year alone has seen the launch of five major industrial projects exceeding 10 billion CNY, including Semicron Phase 4 and Rongjie.

Gasgoo Munich-Striding AI announced on September 29, 2026, that co-founder Yang Yuxin has been appointed president, placing him in charge of global market expansion, ecosystem development, and commercialization.

A Tsinghua University graduate, Yang previously served as chief marketing officer at Black Sesame and as a director and vice president at ThunderSoft. During his tenure at Black Sesame, he focused on marketing, capital operations, and business development. Notably, on July 29, 2026, Striding AI signed a strategic partnership with Black Sesame to jointly advance the global development of embodied intelligence.

Yao Song, founder and CEO of Striding AI, said Yang brings cross-sector industry experience and a global vision. His appointment is expected to strengthen the company's ability to bridge technology, products, and customers, accelerating the large-scale deployment of embodied intelligence in real-world commercial and industrial scenarios.

Founded in early 2026 by Yao Song, Charoen Pokphand Group, and Tsinghua scholar Yu Chao, Striding AI focuses on physical intelligence. Leveraging World Action Model and reinforcement learning technologies, the company is dedicated to deploying humanoid robots in real-world environments.

Gasgoo Munich-LIANHE completed installation at its Haier Avenue station in Jiaozhou on September 28, 2026. That marks the 10th station the company has deployed across Qingdao in September alone, bringing its regional total to 20.

Image credit: LIANHE

The 10 newly opened stations are Chaohai Auto City, Runquanfu Logistics Park, Lanzhou East Road, North Outer Ring, Pujikou Town, JD Logistics Park, SCO Avenue, Haier Avenue, Luanhe Road, and Zhijie Factory. Each site was up and running within an hour, thanks to standardized equipment and construction workflows that allow rapid deployment to meet energy-replenishment demand.

LIANHE’s Qingdao swap network now spans five districts: Jiaozhou, Chengyang, West Coast New Area, Licang, and Jimo. Sites are clustered along major urban transit corridors and logistics hubs, catering to commercial vehicles that need frequent battery swaps—particularly those in long-haul freight and urban delivery.

Looking ahead, the company plans to push into even more commercial-vehicle hotspots—logistics parks, highway interchanges, freight hubs, and industrial zones. LIANHE aims to operate 100 swap stations in Qingdao by the end of 2026, scaling to 300 by June 2027 as it builds out a high-density swap network.

Gasgoo Munich-On September 30, Saint-Gobain Glass' Wuhu service center officially commenced production. The facility currently handles the production and assembly of front and rear windshields, as well as sunroofs. Looking ahead, it is slated to expand into a major manufacturing hub capable of producing over 1 million laminated glass units annually.

Image credit: Saint-Gobain

Saint-Gobain's move into Wuhu is a direct response to the rapid expansion of Anhui's automotive sector. Data from the National Bureau of Statistics shows Anhui's vehicle output reached 3.69 million units in 2025, including 1.79 million new-energy vehicles (NEVs)—both figures ranking first nationwide. Anchored by Hefei and Wuhu as a "dual-core," the province has attracted major OEMs like Chery, NIO, Volkswagen Anhui, BYD, and JAC, with the parts supply chain clustering alongside them.

Wuhu serves as both Chery's stronghold and a critical pivot for the provincial industry. For components like auto glass—which require close coordination on vehicle development, quality validation, and consistent delivery—locating production and service capabilities near the customer directly slashes logistics lead times and response cycles.

According to Saint-Gobain, the Wuhu center went from ground zero to mass production in just two months. Eloi Guenet, President of Saint-Gobain Auto Glass Asia-Pacific and China, emphasized the company's operational mantra: "First is safety, second is quality, third is development." Commercial Director Liu Yang summed up the strategy more simply: "Where the customer is, our capability should be."

Saint-Gobain Auto Glass already operates production bases in Shanghai, Qingdao, Wuhan, and Meizhou, alongside numerous service centers situated close to OEMs. Its Wuhan factory adopted a similar approach, adding capacity to better serve regional clients.

The significance of the Wuhu project, therefore, extends beyond simply adding a service outlet. With plans in place for a million-unit laminated glass capacity, Saint-Gobain is evolving its localized delivery capabilities into full-fledged manufacturing. It is a microcosm of the broader trend: as Anhui's vehicle output surges, suppliers are increasingly converging on the OEM clusters that drive them.

Gasgoo Munich-on Sept. 23, a launch event for hydrogen two-wheelers was held at the University of Shanghai for Science and Technology. The event spotlighted a project under Shanghai's Key Technology R&D Plan "New Energy" initiative, focused on fuel cells and solid-state hydrogen storage systems for hydrogen two-wheelers and embodied robotics. Ten hydrogen two-wheelers, developed by SHPT and its partners, were unveiled — marking the city's first batch-scale research project for such vehicles.

The unveiled vehicles pack a 400W fuel cell system with an enclosed air-cooled design. The system lasts up to 3,000 hours, and the two-wheelers deliver a range exceeding 100 km.

Under the project roadmap, the 10 demo vehicles are slated for deployment at the National University Science Park affiliated with the University of Shanghai for Science and Technology. Small-scale trials in closed scenarios will help accelerate tech iteration and validate use cases. The broader initiative targets deploying at least 400 hydrogen two-wheelers across Shanghai — a move designed to drive wider adoption and close the commercial loop for the vehicles in the city and beyond.

Gasgoo Munich-Chinese automaker GAC Group is evaluating options to add local production capacity in Europe, according to reports. Cédric Lacour, deputy CEO of GAC's French subsidiary, confirmed the company is exploring ways to expand its European footprint — including potential partnerships with Magna and other investors — to establish local manufacturing capabilities for the long term.

On the product and distribution front, GAC aims to roll out 12 fully electric and hybrid models in France by 2030. To support that lineup, the automaker targets 50 dealership locations in the country by 2026, scaling to 200 by the end of the decade — a crucial step in transitioning from a market entrant to a scaled-up European brand.

Magna currently builds GAC vehicles under contract at its Graz plant in Austria. Mobility Global forecasts output there at roughly 5,800 units in 2026, before ramping to about 10,500 units annually. The European Union's tariffs on China-made cars, meanwhile, are a key driver pushing GAC to accelerate its local production plans.

Looking at the broader business, Mobility Global projects GAC’s overall output will climb from roughly 787,000 vehicles in 2026 to over 900,000 by 2030 — even without counting any new European capacity.

Gasgoo Munich-MHERO’s luxury intelligent all-terrain SUV, the MHERO X700, officially opened for pre-sale on September 28, 2026, with prices starting at 249,800 yuan.

Image credit: MHERO Auto

The MHERO X700 features a boxy silhouette. Officially, the model is positioned to bridge daily urban commutes with rugged off-road adventures, catering to diverse driving scenarios.

On the same day, actress Nazha joined the X700’s pre-sale campaign as its "chief acceptance officer."

Gasgoo Munich-Shanghai’s commerce commission is extending its instant lottery system for trade-in subsidies on home appliances and automobiles. The program for appliances, digital products, and smart devices kicks off immediately and runs through December 31, 2026. Meanwhile, the car trade-in lottery opens on October 1 and continues through the end of the year.

Open to individual residents in Shanghai, the appliance and digital product lottery allows one entry per category daily via designated service apps. Winners receive subsidy vouchers immediately upon selection. These vouchers are strictly for personal use—resale is prohibited—and cannot be applied to group-buying deals, prepaid card top-ups, or deposits. Each voucher covers a single item per order, with no cash value or change given.

For vehicles, the lottery window runs from October 1 to December 31, 2026. Eligible residents can register daily between 7 a.m. and 10 p.m. through the official "Shanghai Commerce" platform. The system integrates with the State Taxation Administration’s national invoice verification platform to validate new vehicle invoices in real time. Winners with verified invoices qualify for subsidies and can choose between scrapping their old car or trading it in after the draw—no prior selection is required during registration.

Lottery winners must submit their subsidy applications by January 10, 2027. Those opting for scrapping should use the national vehicle circulation management system or the "Car Trade-in" mini-program, while trade-in applicants can use the "Shanghai Commerce" platform or "Che Xin Meng." Any corrections or updates to the information must be completed through the original channels by January 20, 2027; otherwise, the application will be rejected.

For appliance vouchers, failure to use them before expiration results in forfeiture, though consumers remain eligible for future lotteries. In the event of a full refund, the payment amount is returned to the original source, and the voucher is reinstated the next day with its original validity—unless the voucher had already expired or the refund occurred on its final day. Partial refunds trigger proportional reimbursements without voucher reinstatement, while transaction reversals allow for same-day voucher recovery.

Gasgoo Munich-on September 30, NIO Power brought 28 new stations online, comprising 19 battery swap stations and 9 supercharging stations.

Image source: NIO

The newly deployed battery swap stations carry serial numbers NO.4137 through NO.4155, while the supercharging stations are numbered NO.3459 to NO.3467. Strategically, the new sites span service areas along the G25 Changshen, G40 Hushan, G5 Jingkun, and G45 Daguang expressways. They are also located in more than a dozen cities including Shanghai, Suzhou, Wuxi, Zhengzhou, Yinchuan, Quanzhou, Nanping, Zigong, Yibin, Qingdao, Weihai, Qingyuan, Huaihua, Zhuhai, and Dali. This expansion simultaneously tightens both intercity and urban charging networks.

As of September 30, NIO’s nationwide network totaled 9,492 charging and swapping stations. That figure includes 4,155 battery swap stations—1,071 of which are located along highways—along with 5,337 charging stations and 30,780 charging piles. The company has also established 92 scenic charging routes and integrated over 1.736 million third-party charging piles. Cumulative battery swap services, meanwhile, have surpassed 120 million swaps.

NIO stated it will continue expanding its charging and swapping network.

Gasgoo Munich-Foton Motor officially rolled out its 15th Five-Year strategic development plan on Sept. 29, laying out core business targets and execution paths for the next half-decade. At its center: a goal to sell 1 million vehicles by 2030. To hit that mark, the company will lean on synergies across four main pillars — complete vehicles, smart driving and unmanned equipment, core components, and the aftermarket — while continuously sharpening its industrial structure and ecosystem.

On the global front, Foton plans to pivot from simply exporting products to shipping entire systems, smart manufacturing capabilities, and brands — a leap toward higher-quality overseas expansion. Across international markets, it will push a multi-brand synergy model spanning Foton, Forland, and Kavan. From January through August 2026, overseas sales climbed 44.3% to nearly 150,000 units, pushing cumulative foreign deliveries past 1.39 million. The company has now set a specific 2030 target: 400,000 overseas sales, making up 40% of total volume.

Image Credit: Foton Motor

In new energy, Foton is pursuing a diversified tech route — pushing pure electric, hybrid, and hydrogen fuel-cell powertrains in parallel. It leans on its self-developed AEC three-electric platform to boost in-house production of core modules like battery packs and electric drive axles. New-energy sales surged 50% year-on-year in August 2026, while overseas exports of those models kept growing above 60%. By 2030, Foton aims to sell 500,000 new-energy vehicles — exactly half its total volume.

On the smart-tech front, Foton has rolled out Cangqiong, a large AI model brand for commercial vehicles, marking a self-research breakthrough in integrating smart driving and smart cabins. The company is pushing full-stack, in-house development of L2-to-L3 autonomous driving algorithms and scaling their deployment. It is also deploying L4 high-level autonomous driving in closed settings like ports and mining parks. By 2030, Foton aims to have L4 autonomous tech fully commercialized.

To back this strategy, Foton will balance scale expansion with quality gains — and revenue growth with efficiency gains — throughout the 15th Five-Year period. It will continuously iterate and deepen three core strategies: full internationalization, full new-energy transition, and full smart-tech integration. That push is meant to shift Foton's development model toward a fully formed, industry-leading system across all domains — powering its sprint to the 1-million sales target.

Gasgoo Munich-On September 28, AMD announced a definitive agreement to acquire World Labs, founded by Fei-Fei Li, in an all-stock transaction valued at approximately $8.2 billion. The deal, which still requires regulatory approval, is expected to close by the end of this year. World Labs focuses on spatial intelligence and world models; upon completion, Li will join AMD as executive vice president and chief scientist.

A chip company renowned for its CPUs and GPUs is now integrating a model research team into its technological landscape.

Elsewhere, GlobalFoundries is extending beyond wafer manufacturing. In August 2025, it completed the acquisition of MIPS; this June, it also snapped up Synopsys' ARC Processor IP business. RISC-V processor IP, software tools, custom design, and manufacturing are now being folded into a unified "software-to-silicon" ecosystem.

AMD is shifting from chips to models, while GlobalFoundries moves from manufacturing to IP and software. The directions differ, but they point to a shared shift: AI is migrating from the digital realm into the physical world.

Cars must judge the road on their own; robots need to reach out and grasp objects; industrial equipment must adjust movements in real time based on their surroundings. Once AI truly starts "doing," the chip industry's once-clear boundaries make the old division of labor impossible to maintain.

A Single Big Chip Can't Contain Physical AI

To grasp this shift, we first need to see what new challenges Physical AI poses for chip design.

MIPS CEO Sameer Wasson describes Physical AI as a closed loop of "perception, reasoning, action, and communication." Sensors observe the real world, processors handle understanding and inference, and control systems translate those results into movement—whether for motors, steering wheels, or mechanical joints—all while nodes communicate continuously.

The easiest misconception is treating AI upgrades as simply swapping in a larger GPU or NPU.

Wasson’s assessment is precisely the opposite. Large, centralized processors will persist, but vast amounts of low-power intelligence will also be distributed across sensors, MCUs, actuators, and communication nodes. Centralized computing and distributed intelligence are set to coexist for the long haul.

The automotive industry has already run through this script.

In recent years, electrical and electronic (E/E) architectures have steadily shifted from distributed ECUs to domain controllers, central computing, and zone control. Yet radar, cameras, high-speed comms, power management, and safety MCUs haven't vanished—they've simply evolved.

GlobalFoundries Senior Vice President Faisal Saleem reveals that while the number of vehicles powered by GlobalFoundries chips has held steady at roughly 9 million over the past five years, the chip count per vehicle continues to climb.

GlobalFoundries Senior Vice President Faisal Saleem; Image Source: GlobalFoundries

Robots embody this stratification even more thoroughly.

Large models can understand "bring me the cup," but the motor loops, force control, balance, and collision detection across dozens of joints can't wait for a slow-thinking model. One handles high-level tasks; the other manages millisecond-level actions. They are fundamentally different workloads.

That is why MIPS repeatedly emphasizes "workload-native" design. Confronted with Physical AI, it isn't trying to handle every task with a single processor. Instead, it splits computing needs into AI inference, real-time response, and safety-critical computing. That said, the race for raw computing power hasn't stopped—its NPX6 AI accelerator boasts a nominal performance of 3,500 TOPS.

Viewed together, these two trends reveal a compelling dynamic.

The compute race isn't over—it's just that in the era of Physical AI, raw power is becoming the entry ticket, not the solution itself.

The shifts extend even to power delivery. Answering a question from Gasgoo about 48V architectures, Faisal noted that as power consumption rises for central CPUs, ADAS, and zone controllers, the transition from 12V to 48V systems is "inevitable and imperative"—even if the switch will take time.

When AI truly begins to control the physical world, running the entire system becomes far harder than simply building a more powerful chip.

Systems Grow More Complex, Pushing Chip Companies Outward

As system-level challenges multiply, suppliers naturally refuse to settle for selling just one small piece of the puzzle.

At a recent media briefing, Sameer Wasson made it clear: MIPS aims to evolve from an IP vendor into a full-stack technology solutions provider, with custom chips becoming a cornerstone of its future business.

Even more telling was his follow-up remark: IP licensing remains MIPS’s core business, but a significant portion of future market growth and revenue will come from chip manufacturing and post-tape-out customer delivery.

MIPS CEO Sameer Wasson; Image Source: GlobalFoundries

The business logic is straightforward.

Selling an IP captures value at one point in the chain. Extending into software, custom design, and final chip delivery embeds the supplier deeper into the customer's development cycle.

By its own metrics, MIPS is currently the world’s largest RISC-V IP supplier and the second-largest processor IP vendor globally, trailing only Arm. Its technologies ship in roughly 3.5 billion chips annually, with more than 200 million chips sharing the same microarchitecture already deployed in ADAS systems. Its client roster exceeds 500, including 9 of the world’s top 12 automakers and all of the top 5 robotics and industrial automation firms.

So what MIPS is changing now isn't just its product catalog—it's the depth of its engagement within the system.

GlobalFoundries' acquisitions of MIPS and ARC follow the same logic. Once focused on manufacturing, it is now integrating processor IP, software tools, and custom chip capabilities into its ecosystem. AMD, approaching from the other direction, is pulling world model and spatial intelligence research into the chip company.

It isn't that chip companies suddenly want to do "full-stack"; it's that customer problems no longer reside within a single chip.

Technical complexity pushes companies up and down the supply chain, while new revenue streams make the expansion worth the effort.

Automotive and Robotics Sectors Are Starting to 'Borrow' Tech

As companies extend vertically, technology is flowing horizontally.

On September 8, XPeng officially launched its automated robotics production line, where the IRON robot walked off the line autonomously after assembly. According to XPeng, IRON features 76 degrees of freedom and carries three Turing AI chips delivering 2,250 TOPS of effective compute. The quality systems and manufacturing capabilities honed in its automotive business have been transplanted directly to the robotics line.

This is a classic case of internal reuse. With cars, AI chips, models, and robots all under one corporate roof, the technology and manufacturing foundations already invested in automotive can be amortized across robotics.

Independent robotics firms, however, are taking a different path.

UBTech currently relies on established computing ecosystems, but this June it co-founded Xixuan Chuangzhi with firms like Maxio. With a registered capital of CNY 100 million, the venture is developing dedicated chips for embodied intelligence on the edge, targeting tape-out in the second half of 2027 and mass production in 2028.

Using mature platforms to build products first, then circling back to influence chip definition once workloads, costs, and scale become clearer—that is also a valid strategy.

Conversely, automotive chipmakers are moving into robotics.

SemiDrive has assembled a robotics chipset portfolio featuring the R1 "brain," D9 "smart control cerebellum," and E3-R execution control MCU. Its website indicates that the D9-Max is already in mass production at leading humanoid robot manufacturers.

SemiDrive Vice President Zhang Xitong said at the CIFTIS trade fair in September that in SemiDrive’s view, automotive chipmakers entering robotics can "reuse 70% to 80% of their capabilities." Yet its own product evolution shows that reuse isn't a simple copy-paste: when it comes to joints, dexterous hands, and motion control, redesigns around new workloads are still required.

Safety capabilities are migrating, too. This June, NVIDIA launched Halos for Robotics, extending the Halos safety framework honed in autonomous driving to humanoid and industrial robots. Agility Robotics became the first partner to integrate elements of this capability into its own robot safety systems.

XPeng brings chips and manufacturing from cars to robots; UBTech moves upstream from robotics to define chips; SemiDrive repurposes automotive-grade capabilities for robot products; and NVIDIA extends automotive safety frameworks into robotics.

Technology can be reused across industries, but complete systems cannot simply be transplanted.

Underlying capabilities are increasingly like a set of public building blocks, but every new terminal requires them to be reassembled from scratch.

Full-Stack Has Limits, and Openness Comes at a Cost

If the story ended here, the conclusion would be simple: every company will become increasingly "full-stack" in the future.

Reality, of course, is not that simple.

Suppliers must first confront their own capability limits.

In 2018, GlobalFoundries paused 7nm FinFET development to divert resources toward differentiated processes like FDX, RF, and analog mixed-signal. Today, acquiring MIPS and ARC extends its reach into IP, software, and custom design based on existing strengths—rather than re-entering the fray across all advanced logic nodes.

Nor will customers naturally accept an increasingly closed platform.

This January, an automotive open-source initiative led by the VDA and Eclipse expanded to 32 companies, aiming to build an open, interoperable software foundation. In May, Automotive Grade Linux launched the SoDeV reference platform, with a core goal of decoupling software development from specific hardware platforms.

This creates direct tension with the full-stack expansion of chip companies.

Suppliers want to tightly integrate IP, chips, runtimes, toolchains, and even models. This reduces integration overhead, shortens development cycles, and boosts revenue.

OEMs, however, see the flip side: if chips, compilers, middleware, and safety systems are all bundled together, switching suppliers next time won't mean just "swapping a chip"—it will mean redoing the software and verification from scratch.

A complete solution buys efficiency; a closed ecosystem exacts a price.

RISC-V brings this contradiction into sharper focus.

MIPS CTO Yankin Tanurhan warns that if companies build extensive proprietary extensions before unified standards are settled, they may be forced to rework and re-adapt once the official standards are locked in.

But RISC-V's entry into automotive is no longer just theoretical. Infineon, the leader in automotive MCUs, has announced it will launch a RISC-V product family within its AURIX lineup. Quintauris—a joint venture founded by Bosch, Infineon, Nordic, NXP, Qualcomm, and STMicroelectronics—is advancing a RISC-V reference architecture for automotive real-time computing, and MIPS is already collaborating with the group.

China's automotive industry is also catching up on standards. The first industry standard for RISC-V in automotive is currently being drafted, with dozens of companies participating.

The question used to be whether RISC-V could "make it into the car." Now, the more practical question is whether different companies can get in under the same set of rules.

Openness does not mean a lack of standards. On the contrary, the more open the ecosystem, the more it needs a set of standards that everyone is willing to follow.

Once robots truly enter mass production, they will face the same hurdle.

Today, mature platforms allow for the fastest path to a working machine. Tomorrow, as shipment volumes rise, power consumption, BOM costs, real-time control, and algorithm loads will force companies to recalculate: what to keep buying, what to co-define, and what to hold in-house.

Physical AI hasn't rendered the traditional division of labor obsolete, but it is forcing every company to find its place anew.

Some move from manufacturing to IP, others from chips to models. Some bring automotive tech into robotics, while others circle back from robotics to define chips. Meanwhile, standards, open source, and multi-supplier systems are constantly drawing new boundaries around this expansion.

The more complete the platform, the more customers demand a clear exit strategy.

Physical AI is redrawing the boundaries of the chip industry.

In the next stage, the real story won't be about who can control the entire supply chain.

It will be about who has the power to decide where the industry divides its labor next.

Gasgoo Munich-"I don't believe AI will directly trigger mass layoffs, but many companies are repackaging business-driven headcount optimization as an AI-fueled transformation." Liu Songbo, vice dean of the School of Labor and Human Resources at Renmin University of China, recently discussed talent shifts in the auto industry amid the AI wave, calling the practice "AI-washing layoffs."

In February, Gallup surveyed 23,000 American workers; 660 of them remained unemployed after losing their jobs. Among this group, only about 1% pointed to AI as the direct cause of their unemployment. Far more blamed organizational restructuring, cost-cutting, or the broader economic environment.

The auto industry has been pushing AI transformation while simultaneously adjusting headcount in recent years. Because the two trends overlap, they are easily conflated. That overlap is the crux of Liu's argument: AI will jolt employment, but the underlying business shifts within companies deserve just as much attention.

AI accounts for only a sliver of corporate layoffs

Job losses tied to AI are already a matter of public record.

In early 2026, fintech firm Block announced layoffs of roughly 4,000 employees—over 40% of its workforce. In an open letter, the CEO noted that AI tools had reshaped how the company is built and runs, allowing smaller teams to accomplish more than before.

Oracle's case is even more explicit. In fiscal 2026, its headcount fell from roughly 162,000 to 141,000—a drop of about 21,000 in a single year. In its annual report, Oracle stated outright that adopting and deploying AI in operations has led to, and may continue to lead to, workforce reductions. At the same time, the company cited management shifts, product changes, strategic adjustments, and mergers as contributing factors.

Image source: Generated by Doubao

The auto industry is seeing similar shifts in roles.

In May 2026, General Motors cut about 600 IT staff—more than 10% of its IT department. The company said it was transforming its IT organization to better position itself for the future. Yet insiders say GM is simultaneously hiring IT talent with stronger AI capabilities.

This means a single company can eliminate some roles while adding others. The real shift is in the structure of jobs.

That dynamic tends to emerge whenever AI enters an organization. As AI boosts efficiency in certain tasks, demand for some roles drops—yet companies simultaneously add new technical capabilities. Most layoffs, however, are tied to the company's operating conditions. The auto industry is squarely in that environment right now.

According to the National Bureau of Statistics, auto manufacturing profits totaled 195.35 billion yuan in the first half of 2026, down 19.5% year on year. Shrinking margins force companies to rethink costs and resource allocation. Product lines, R&D projects, production scales, and staffing all feel the impact.

That pressure is already playing out in real moves. Domestic automakers rarely publicize "layoff" figures; instead, they idle inefficient capacity, scale back operations, reshuffle staff internally, or offer voluntary separation packages.

GAC Honda, for instance, closed its aging gasoline-car plant in Huangpu, Guangzhou. For the thousands of affected workers, it relied mainly on internal transfers to its new-energy vehicle plants and voluntary separation payouts. Meanwhile, the Ministry of Industry and Information Technology is pushing out outdated capacity; several legacy automakers in financial distress have idled production bases or exited the market by shedding dormant lines.

Notably, the industry is splitting sharply: as some companies pull back on capacity and headcount, leading players like BYD and Geely are still mass-hiring fresh graduates and expanding their talent reserves.

Image source: Volkswagen Group

Overseas automakers show a similar pattern. Global carmakers like Mercedes and Stellantis are also cutting jobs, while top-tier suppliers such as Bosch, ZF, and Continental are all streamlining organizations and trimming staff.

Based on available public information, the driving forces behind this round of capacity and staffing adjustments—both at home and abroad—center on market competition, price wars, and profit pressure. No automaker has officially cited AI as a reason for cutting staff or closing plants.

Liu's remarks target precisely this reality. He isn't denying AI's impact on employment; rather, he's warning companies against lumping all business-driven headcount optimization under the "AI layoffs" label. Li Linfeng, CEO of Haiwei Technology, also stated that AI and layoffs are not correlated.

The real question worth exploring is what specific tasks are actually changing once AI enters these companies.

As AI moves in, workflows shift first

When AI enters a company, the most visible changes are the individual tools.

Li Ning, vice general manager of the quality department at Changan Automobile, previously noted that the company uses an AI assistant to review supplier rectification reports. Tasks that used to take a human 30 minutes now wrap up in roughly two minutes.

Such tasks are tailor-made for AI. Rectification reports are packed with fixed formats and repetitive information. AI can rapidly parse the text, flag issues, compare pre- and post-rectification details, and hand off only the items requiring human review to engineers. Machines process the information; humans judge the results. The old workflow gets dismantled and rebuilt.

This is far closer to what actually happens inside companies than the narrative of "AI replacing a job." A quality engineer's role hasn't vanished into thin air, but a chunk of their time is now freed from organizing documents, hunting for information, and making repetitive comparisons. Similar shifts are rippling through R&D, procurement, customer service, finance, and IT.

Image source: Generated by Doubao

The problem comes next. If every department simply deploys a few AI tools, the company ends up with a batch of more efficient "point solutions." The original cross-departmental processes remain unchanged, data stays siloed, and staff divisions barely shift. AI has merely sped up a few isolated steps.

Deloitte Consulting has spotted this pattern. A report from the firm notes that over 80% of mainstream automakers have launched generative AI pilots, yet only about 15% have scaled those applications. Deloitte dubs this the "pilot dilemma"—the core issue being that AI apps are scattered across different scenarios and lack integration with existing business processes.

Take Changan's AI practice: the supplier rectification report is just an entry point. Once AI reads the report, subsequent steps—issue extraction, rectification tracking, quality data accumulation—should all flow into the same pipeline. AI handles the standardized information processing, freeing engineers to spend more time on problem assessment, supplier communication, and final decisions.

Change just one step, and you're no longer merely transforming "report review"—you're reengineering an entire quality-management workflow.

One global auto parts supplier uses multiple AI agents to interpret ERP and IoT data, automatically executing parallel tasks such as cross-shift production scheduling, alternative material recommendations, and equipment maintenance. After each execution, the system self-optimizes its task decomposition and resource weighting based on feedback, creating a continuous learning loop.

Then there's Geely. It has deployed over 160 AI role assistants and more than 600 AI skills, executing tasks over 130 million times. The automaker estimates the annual direct and indirect economic benefit exceeds 1 billion yuan. This is a far cry from using a standalone AI assistant. The latter tackles a single task; the former starts taking over an entire process.

For automakers, this is where AI begins to reshape the organization. A business process that once required multiple roles to work in relay—someone gathering data, someone organizing materials, someone analyzing issues, someone initiating workflows, someone following up—can now be streamlined. Once AI steps in, standardized links get compressed or automated, and human work gradually concentrates on judgment, coordination, and decision-making.

Image source: Generated by Doubao

Wang Xianbin, vice president of the Gasgoo Auto Research Institute, argues that AI's reshaping of the auto supply chain isn't piecemeal—it spans the entire chain. From product definition and R&D design to manufacturing, supply chain management, and after-sales service, AI is permeating every link. Yet an "AI-defined vehicle" isn't just about layering AI tools onto each step; it requires rebuilding the entire business process and organizational structure.

Consequently, the shifts in staffing structures driven by AI will grow far more specific.

Workloads in some roles will shrink, responsibilities in others will pivot, and entirely new positions will emerge. Changan, for example, has adjusted its hiring and talent strategy this year. Public information shows the automaker has prioritized intelligence, new energy, and software as key talent areas, with its 2026 campus recruitment plan projected to expand by more than 30%.

Industry-level data reflects this shift as well.

Zhaopin's "2026 Human Resource Management Trends Report" shows a supply-demand ratio of 3.08 for AI engineers—meaning roughly three job openings for every applicant. The ratio for automotive design and manufacturing engineers stands at 2.38, also signaling a tight talent market. The report also notes a sharp uptick in hiring demand for roles related to large language models and autonomous driving.

Within the auto sector, this structural deficit is even starker. In 2025, the new-energy vehicle industry faced a talent gap of 1.03 million people. R&D talent for electric powertrains and intelligent driving is especially scarce: the supply-demand ratio for autonomous-driving engineers is just 0.38, meaning roughly three roles are competing for one qualified candidate.

Gasgoo's previous reporting on the issue echoes this: automakers' shortages no longer stop at traditional software engineers. Finding talent who understands vehicles, algorithms, and data—and can embed that technology into specific automotive scenarios—is growing ever harder.

So the true change AI brings ultimately boils down to something highly concrete: for any given task, who will do it, which steps they will handle, and how broad a scope one person can cover.

The skills individuals need to build are already shifting

AI's impact on individuals is already showing up in how companies hire and train.

Hiring standards are adjusting. Geely brought on over 4,000 fresh graduates in 2026. XPENG plans to raise the share of campus hires from 50% to 70%, reasoning that younger workers adopt new tools and learn faster. Changan and some other automakers have even spun off their industry-education integration operations into standalone entities, embedding real-world corporate needs into school curricula ahead of time.

Job requirements are evolving too. Li Zhele, secretary-general of the Auto Talent Professional Committee under the China Talent Research Association, has outlined how the auto talent competency model is changing: where problem-solving sufficed before, complex problem-solving is now the baseline; learning ability has given way to rapid learning; and imitation-driven innovation is increasingly replaced by the demand to innovate first.

An in-vehicle display engineer, for instance, used to focus on hardware, structure, and display tech. As smart cabins evolve, they now need to grasp chips, software, algorithms, and user experience. Someone handling overseas business must simultaneously navigate product, regulatory, channel, and local market dynamics.

This skill set defines the "all-around employee"—the versatile, cross-functional talent everyone talks about. In the AI era, such workers need enough logical rigor and knowledge breadth to act as business architects and coordinators, deploying AI agents to shoulder heavy execution work. Crucially, though, humans must still be able to judge the reliability of AI outputs.

Image source: Generated by Doubao

Haiwei Technology has reportedly baked these requirements into its roles. CEO Li Linfeng sketched a possible future work model: a standout employee could direct 30 to 50 AI agents, taking on the workload of an entire business unit. Such an employee must first grasp the "silicon-based" work logic, then possess sufficient logical ability and knowledge breadth.

This means AI proficiency is migrating from a specialized skill for tech roles to a baseline capability across a much wider range of positions.

但这并不意味着所有人都要变成AI工程师。

An R&D engineer can have AI generate multiple technical proposals, but the final choice still hinges on cost, performance, reliability, and project timelines. A product manager can use AI to sift through reams of user feedback, yet deciding which features to build still comes back to product positioning. An overseas business lead can let AI analyze local markets, but still must personally evaluate partners, channels, and the commercial environment.

Discussing AI's limits, Liu noted that the technology excels at processing standardized, procedural information and tasks. But value judgments, timing calls, and bottom-line decisions in complex scenarios still require a human—someone who can shoulder responsibility and pressure.

The auto industry happens to be full of such work. R&D staff must trade off technology against cost; quality teams must diagnose issues based on on-site conditions; managers must balance competing departmental interests; and once a company expands overseas, variables like regulations, culture, and business customs multiply.

Changan's experience in Thailand illustrates the real-world demand for such composite skills. Entering the local market, the company confronted more than just product and technology issues—Chinese and local employees also held different views on overtime culture.

The threshold for an all-around employee isn't "knowing everything." It's about ensuring your knowledge boundaries don't stay trapped inside one familiar niche. AI lowers the barrier to cross-disciplinary learning, and individuals need to gradually widen their own capability ranges.

Liu's advice to avoid "excessive anxiety," applied to the individual, means there's no need to rush into guessing whether AI will replace you. Instead, make AI a tool in your workflow while continuing to build your professional expertise and judgment.

The first step is simply to start using AI—and make it work for you.

Gasgoo Munich- BAIC Group has officially pulled back the curtain on the Xingtan 5X, a new boxy five-seat SUV under its umbrella. As the first model in Beijing Off-road's fresh new-energy lineup, the Xingtan 5X is a global product slated for overseas markets.

The target buyer blends weekday commutes with weekend outdoor escapes. The SUV takes on urban light-off-road and boxy EV rivals, leaning on interior space, features, and its angular silhouette as key differentiators.

Image source: Gasgoo on-site photography

Dimensionally, the Xingtan 5X spans 4,865 mm long, 2,000 mm wide, and 1,910 mm tall. Throw in the external spare tire and length stretches to 5,005 mm. The wheelbase sits at 2,875 mm.

The design merges rigid and refined boxy lines, capped by a flat roof. Buyers can spec eight exterior colors and three interior shades. Cabin space utilization hits roughly 88.6%, and folding the front seats creates a 1.75-meter flat surface.

Tech highlights include dual 15.6-inch 2.5K center screens powered by a Qualcomm Snapdragon chip. BAIC teamed up with the National Centre for the Performing Arts to tune the 23-speaker audio system. A dual-opening compressor fridge handles temperatures from -6°C to 50°C and opens from either side.

For driver assistance, the Xingtan 5X runs Huawei's ADS 5 Pro setup with an in-cabin LiDAR. The sensor suite adds millimeter-wave radar, HD cameras, and ultrasonic units. It now supports 120-meter trail-assist reversing — and keeping the LiDAR inside the cabin helps shield it from outdoor grime.

Image source: Gasgoo on-site photography

On safety, the SUV uses a one-piece laser-welded high-strength steel cage structure. It carries an IP68 rating, meaning it can sit in 1.5 meters of water for two hours without leaking.

Powertrains span both pure electric and hybrid variants. The EV packs an 81.9-kWh battery for a 625-km range; the hybrid holds a 50.4-kWh battery good for 310 km of electric-only driving. Both support external power discharge. Off-road specs include a 25-degree approach angle, a 28-degree departure angle, 228 mm of ground clearance, and a 600-mm wading depth. Fifteen drive modes are on tap, with physical function buttons mounted on the roof.

Image source: Gasgoo on-site photography

As for the rollout, Gasgoo understands that display vehicles will reach showrooms before the National Day holiday, with pre-sales expected in mid-October. The variant running Huawei Qiankun intelligent driving will start around 170,000 yuan. Going by industry norms and past pricing patterns, the official launch price could still drop by roughly 10,000 yuan — though final figures will depend on the official announcement.

Gasgoo Munich-On the evening of September 28, GAC Group unveiled a major asset restructuring plan, proposing to acquire the 50% stake in FAW Toyota held by FAW Group through share issuance. The following day, China FAW and GAC Industrial formally signed a strategic cooperation framework agreement. GAC Group's stock surged by the daily limit upon resuming trading.

This is a strategic alliance tied by equity, aimed at revitalizing existing joint venture assets. Once the transaction closes, GAC will replace FAW as the Chinese partner in FAW Toyota, creating a new "GAC plus Toyota" dual-JV landscape alongside GAC Toyota.

By swapping its FAW Toyota stake for shares in GAC's listed entity, FAW avoids cash outlays and is set to become the group's second-largest shareholder. Guoyuan Securities describes the deal as a "share-for-share" style "light integration," further binding the two parties' fortunes together.

A New Playbook for SOE Integration

From the stalled merger of Dongfeng and Changan last year to this GAC-FAW focus on joint ventures, the approach to integrating state-owned automakers is shifting.

Past attempts involved full group mergers—zero-sum games tangled by control rights, administrative ranks, regional interests, and job placement. In 2025, Dongfeng and Changan announced plans to restructure only to suspend them 100 days later. Industry analysts cite mismatched administrative hierarchies, local government wrangling over headquarters, and employment issues as the main roadblocks.

Image Source: China FAW

Now, the focus is on targeted joint venture consolidation. By cross-holding equity to align interests, both sides get what they need—a win-win that fits market logic and proves far more workable.

For Toyota, this marks a shift from a dual-track balancing act to unified operations in China. Long divided between two Chinese parent systems, FAW Toyota and GAC Toyota operated with separate product planning, sales channels, and marketing strategies. That "two-car strategy" fueled rapid expansion when the market was booming. But as growth slows into a battle for market share, the redundancy—duplicate R&D for sister models, price conflicts, and channel cannibalization—has become a drag on efficiency.

Image Source: Toyota China

Citi estimates that if the northern and southern Toyota arms achieve synergy, they could form a unified Toyota China platform capable of producing 1.2 million to 1.3 million vehicles annually. By optimizing product planning to cut internal competition among shared-platform models, joint purchasing could shave costs by roughly 2 to 3 percentage points. Meanwhile, integrating dealer networks might reduce selling and administrative expenses by another 1 to 2 percentage points.

Under unified operations, Toyota can coordinate product planning, slash duplicate R&D spending, optimize channel layouts, and synchronize brand messaging. On the supply chain side, the company can tap into GAC's localized component ecosystem to boost bargaining power and drive down BOM costs.

Crucially, Toyota has already unified its R&D structure in China. At the 2025 Shanghai Auto Show, Toyota China's general manager, Li Hui, formally introduced the "ONE R&D" system. This initiative integrates the R&D forces of FAW Toyota, GAC Toyota, and BYD Toyota, shifting decision-making power for Chinese market models from Japanese headquarters to local teams.

For GAC, FAW Toyota is a high-quality asset with strong earning power. The Toyota joint venture remains a cash cow, and its direct consolidation will significantly boost GAC's investment returns. At the same time, bringing in FAW—a central state-owned enterprise—as a strategic shareholder offers advantages in policy resources and industry chain coordination.

For FAW, the deal preserves stable dividend income from the joint venture sector while opening a gateway into new energy vehicle (NEV) investments. By taking stock instead of cash, FAW swaps part of its FAW Toyota stake for GAC shares, ensuring profits from the Toyota JV remain within the FAW ecosystem through the equity chain.

More importantly, FAW addresses its own weakness in the NEV transition. Analysts at Gasgoo Auto Research note that FAW's proprietary NEV efforts have yielded limited results; the northern climate is naturally tough on EVs, its own "FAW Yueyi" brand has made little noise, and the first model from its partnership with Leapmotor still awaits market validation. By directly buying into GAC—a player with a more successful NEV transition—FAW is essentially trading capital for experience and equity for resources.

The Potential for Strategic Synergy

The joint venture business is just the starting point. Deeper synergy lies in R&D, supply chains, and global expansion.

On R&D and supply chains, GAC brings mature capabilities in electronic-electrical architecture, e-drives, batteries, and charging networks, while FAW boasts deep roots in vehicle manufacturing, supply chain layout, and the northern market. Combined scale allows both to spread R&D and infrastructure costs, avoiding redundant investments.

Lang Xuehong, deputy secretary-general of the China Automobile Dealers Association, notes that the equity tie gives both sides a sustained incentive to push technical cooperation forward.

Regarding global expansion, synergy in dealer networks, localized production, and after-sales service could lower individual export costs and boost the overall competitiveness of Chinese automotive brands in the global market.

Image Source: China FAW

BOCI believes the cooperation path designed by FAW and GAC aligns with the current needs of both parties. It offers a blueprint for other state-owned automakers looking to integrate and restructure, while also reigniting capital market expectations for industry consolidation.

If this transaction goes through, will other foreign brands with two Chinese joint ventures follow suit? Could consolidating two JVs into one become the trend?

The answer hinges on two conditions. First, is the pressure on foreign automakers intense enough? Honda and Volkswagen are seeing sustained declines in internal combustion engine vehicle sales, with capacity utilization dropping and idle capacity costs mounting. Although new NEV models have launched, scaling them up takes time, leaving a short-term gap that cannot offset fading ICE profits. In this transitional lull, the internal drive to consolidate redundant investments and boost efficiency is strengthening.

Second, can the interests of Chinese partners be aligned? Honda partners with Dongfeng and GAC; Volkswagen with FAW and SAIC. Each party has its own demands regarding local taxation, employment, production capacity, and brand voice. Integration requires a win-win scenario: foreign partners gain efficiency and cost savings, while Chinese partners secure asset appreciation, strategic synergy, or transition resources. If the balance tips, the deal won't land.

Looking at the longer cycle, state-owned auto integration has reached this point—but what's the next move? In the medium term, "business-level cross-shareholding plus specialized integration" is set to become the mainstream.

This could mean sharing platform architectures in the NEV sector or jointly procuring core parts like batteries. For overseas business, it means integrating global dealer networks to avoid going it alone. In capital-heavy fields like power batteries, autonomous driving, and automotive chips, the push will be toward joint R&D and shared tech platforms—spreading development costs and shortening iteration cycles.

This isn't about one side devouring the other; it's about directing resources where they belong. As the auto industry shifts from growth competition to a fight for survival in a stagnant market, the pressure to integrate will only intensify. And a cooperation model built on equity ties and strategic synergy may well become the dominant paradigm for future state-owned automaker consolidation.

Gasgoo Munich-XPENG recently signed carbon credit trading agreements with Porsche and other international automakers. These cover regulations in the EU, UK, and Australia. The total deal value exceeds 1 billion yuan. XPENG is poised to generate over 500 million yuan from these credits in 2026 alone.

The significance of this partnership extends far beyond immediate financial gain. It marks a fundamental shift for Chinese automakers expanding globally. They are moving from merely adapting to overseas rules to actively helping international peers achieve compliance. They achieve this by leveraging pure-electric sales and carbon management capabilities. Carbon credit trading is emerging as a new synergy between Chinese and foreign automakers.

Fines Drive Urgent Compliance Needs

The fundamental driver behind carbon credit trading is the continuous tightening of emission regulations. Major global auto markets are also strictly enforcing penalty mechanisms.

The impending EU fines are the primary catalyst. Under new regulations effective in 2025, fleet average CO2 emissions for passenger cars must fall to 93.6 grams per kilometer. The penalty is 95 euros for every gram exceeded per vehicle. Industry estimates put potential sector fines as high as 15 billion euros. That figure is enough to force any traditional automaker to reassess its compliance strategy.

Consider Volkswagen Group: its fleet average CO2 emissions for 2025 stand at 100 grams per kilometer—above the EU’s 93.6-gram target. CFO Arno Antlitz said in May that missing emission targets from 2025 to 2027 could result in cumulative fines of 1.5 billion euros. Annual penalties are estimated at 400 million to 500 million euros.

Image Source: Porsche

Porsche's situation is illustrative. The brand is currently refocusing on internal combustion engine vehicles just as its EV sales slump. By the end of June, sales of the Taycan had fallen roughly 20% year-on-year, while the electric Macan dropped about 30% in Europe. Only the new electric Cayenne saw growth, though volumes remain modest. Dataforce data shows Porsche's fleet average CO2 emissions reached 130.2 grams per kilometer through June this year. This is up 9.8% from 118.5 grams in the same period of 2025. Facing the dual pressures of impending fines and a slowing EV transition, Porsche opted to exit Volkswagen Group's internal emissions pool. It formed an open compliance alliance with XPENG. Essentially, the move seeks a compliance path with lower costs and higher certainty.

XPENG's carbon credit cooperation spans multiple regulatory frameworks, including the EU, UK, and Australia. This demonstrates that carbon credit trading is not isolated. It is a systemic market expanding globally in sync. EU regulations allow automakers to form open emissions pools, calculating averages based on their new fleets. High-emission internal combustion and performance brands can leverage surplus credits from pure-electric makers to offset excess emissions and avoid penalties. In March 2025, the EU agreed to assess compliance based on a three-year average from 2025 to 2027, but the targets themselves were not lowered. That means fines are merely deferred, not canceled. This makes the firm demand for carbon credits more pressing as the timeline clarifies.

Why XPENG?

The essence of carbon credit trading is the monetization of technological advantages into carbon assets: the more pure-electric vehicles a company sells, the more credits it accumulates. XPENG's ability to supply in this arena stems directly from the rapid growth of its overseas sales and the premium shift in its product mix.

Data shows that in the second quarter of 2026, XPENG's overseas sales surpassed 20,000 units for the first time—an 81% year-on-year jump. In the first half of this year, overseas revenue accounted for over 25% of the total, with an average selling price exceeding 40,000 euros. Both per-vehicle revenue and gross profit lead among Chinese automakers expanding abroad. From January to July 2026, XPENG ranked first in sales among Chinese new-energy pure-electric brands in countries like Norway, Denmark, France, and Portugal. This demonstrates that XPENG's carbon credit supply relies not on sporadic volume in a single market, but on sustained sales across multiple high-value European markets. The stability and predictability of its credits are significantly superior to those of competitors chasing short-term volume spikes.

Image Source: XPENG

Porsche's choice of counterparty is particularly notable. As one of Volkswagen Group's most profitable brands, Porsche's decision to exit the group's internal emissions pool is significant. It independently formed an alliance with XPENG, suggesting XPENG's offer provides superior cost efficiency and compliance certainty compared to internal allocation. The Porsche-XPENG pool will be managed by Porsche and cover both 2026 and 2027. It is an open pool, meaning other brands or automakers can join.

Other open pools include one managed by Tesla with Ford, Honda, Mazda, and Suzuki. Another is managed by Mercedes-Benz, comprising Volvo, Polestar, and Smart. XPENG's ability to secure Porsche as a partner demonstrates the recognition its carbon credit supply capability has received from mainstream international automakers.

A vice president at XPENG noted that international automakers' choice to partner with XPENG is proof of the company's rising global influence. XPENG has signed multiple strategic cooperation agreements with Volkswagen Group in the past. This track record of successful collaboration has enabled XPENG to partner with more international OEMs.

In fact, Chinese automakers have precedents in carbon credit trading. Leapmotor transferred EU carbon credits to Stellantis in 2025, generating 1.11 billion yuan in related revenue for the year. The cap for its 2026 credit trading has been significantly raised to 2.8 billion yuan.

Analysts point out that carbon credit revenue is not a one-off gain divorced from main operations. It is an added value derived from expanding overseas sales and pure-electric product portfolios. As models like the MONA L03 and XPENG G9L enter international markets, XPENG's tradable carbon credits continue to accumulate, leaving room for further revenue growth.

The Shift in Sino-Foreign Automaker Collaboration

This carbon credit cooperation spans regulatory systems in the EU, UK, and Australia. The industry views it as a case study of the shift from simple product exports to comprehensive exports of products, compliance, and carbon management capabilities. As one industry view holds, "The next stage of going global isn't just about product competitiveness—it’s about understanding global rules."

XPENG's collaboration with international automakers did not begin with this round of carbon credit trading. Since 2023, XPENG and Volkswagen Group have deepened their cooperation across models, platforms, electrical and electronic (E/E) architecture, and charging networks. In 2023, Volkswagen Group acquired a 4.99% stake in XPENG for approximately $700 million to access its software architecture and AI capabilities. In February 2024, the two signed a joint development agreement for platform and software technology. This was followed in April 2024 by an E/E architecture strategic cooperation framework. In January 2025, they began building China's largest super-fast charging network. By March 2026, the first jointly developed model rolled off the production line and opened for pre-orders. It is a full-size pure-electric SUV named "Yuzhong 08," equipped with XPENG's latest VLA intelligent driver assistance system.

This trajectory reveals a key trend: the relationship between Chinese and foreign automakers is shifting. It is moving from the old "market for technology" paradigm to a new "technology + carbon management" two-way output paradigm. Volkswagen needs XPENG's electrification platforms and intelligent technology to accelerate its transition, as well as XPENG's pure-electric sales to optimize its carbon credit accounting. XPENG, in turn, needs Volkswagen's global manufacturing system and brand channels to accelerate its overseas expansion, while also using technical services and carbon trading to diversify its revenue structure. Carbon credit trading represents the most innovative link in this new synergy. It converts the first-mover advantage of Chinese automakers in electrification into quantifiable, tradable carbon assets recognized by the international market.

Porsche's exit from the Volkswagen Group emissions pool may actually lower the group's overall carbon emissions level. Porsche's high-emission vehicles will no longer be factored into Volkswagen's calculations. This strategic adjustment of "governing through separate pools" illustrates that carbon compliance is evolving from internal group coordination toward a flexible, market-based allocation across enterprises and brands.

Diversified Revenue Structure and Long-Term Industry Challenges

While carbon credit trading revenue attracts attention, it represents just one component in XPENG's diversified revenue structure. It also provides a snapshot of the upgraded narrative of Chinese automakers expanding globally.

Image Source: XPENG

Beyond vehicle sales, XPENG is establishing a revenue architecture built on a foundation of complete vehicles, powered by technical services, supplemented by carbon credits, and looking ahead to physical AI. The growth of technical service revenue is striking. In the second quarter of 2026, service and other revenue accounted for only 13.7% of total revenue. However, it contributed 49.6% of gross profit. This income stems primarily from R&D services provided to Volkswagen Group, with a gross margin of 75.1%. The underlying logic of technical services and carbon credit trading is similar. Neither relies on the linear growth of vehicle deliveries. Instead, they "package and sell" the capabilities accumulated in electrification and intelligence. This model allows XPENG to support overall profitability through high-margin non-vehicle businesses even while facing pressure on vehicle gross margins.

Yet it must be clearly recognized that carbon credit income is policy-dependent and difficult to use as a long-term anchor for valuation. In March 2026, the EU changed its assessment method to a three-year average for 2025 to 2027. If targets are further relaxed or carbon pricing mechanisms adjusted in the future, the scarcity and trading value of carbon quotas could shrink. While carbon trading brings substantial extra income, the industry's structural shortcomings are evident beneath the high transaction volumes. One-off credit gains cannot cover the investment required for low-carbon transformation across the entire supply chain. Furthermore, fragmented global carbon accounting standards continue to raise compliance costs for global expansion. Ding Shanshan, Green Supply Chain Project Director at the Institute of Public and Environmental Affairs (IPE), noted the stringent international green trade rules. She urged Chinese automakers to seize this opportunity to accelerate transparent disclosure of product carbon footprints. This would force deep decarbonization across the supply chain.

Meanwhile, the EU's Carbon Border Adjustment Mechanism (CBAM) is gradually moving from formal implementation toward institutional maturity. Although CBAM currently covers basic industrial goods like steel, aluminum, cement, and electricity, the automotive supply chain is highly intertwined with these sectors. Steel is the foundational material for car bodies and structural components, while aluminum is widely used in lightweighting and battery casing manufacturing. This means the impact of CBAM on the auto industry is essentially a systemic cost restructuring transmitted from the material end to the vehicle end.

Thus, the future competition among automotive enterprises will no longer be merely about cost control capabilities, but about supply chain data governance capabilities. Pioneers in carbon credit trading already possess a first-mover advantage in carbon data management and supply chain carbon footprint tracking. The transferable value of this capability will far outstrip the revenue scale of the carbon credit trading itself.

Autoliv has officially opened its new technical center in Wuhan.

This marks the second technical center the global automotive safety supplier has established in China, following its Shanghai hub.

As foreign Tier 1 suppliers in China diverge—many cutting capacity and trimming headcount—Autoliv is bucking the trend by doubling down. What fuels the confidence to deepen its roots in China while others retreat?

Image Source: Autoliv

Shanghai + Wuhan: A "Dual-Engine" R&D Strategy Takes Shape

The Wuhan facility features R&D offices, advanced laboratories, high-efficiency warehousing, and tooling sample rooms. Its operations span the entire chain—from auto safety component development and virtual simulation to testing verification and system integration—fully addressing the diverse R&D needs of clients in automotive safety.

The team currently exceeds 300 staff, with plans to expand to more than 400.

Autoliv previously established its first Chinese technical center in Shanghai. The launch of the Wuhan facility signals the formal completion of a "dual-engine" R&D layout across Shanghai and Wuhan.

Mao Lili, Vice President of Sales, Engineering, Strategy, and Business Development at Autoliv China, told Gasgoo Auto that the two centers will serve surrounding customers and deploy operations based on specific market and client demands.

In Mao's view, the two cities offer complementary strengths. The Shanghai center boasts over three decades of engineering experience, while the Wuhan hub is powered by younger engineers with expertise in emerging fields like AI, bringing fresh energy. The two will exchange technical insights and develop in tandem.

Notably, despite its recent opening, the Wuhan center is already supporting export projects for domestic brands and handling R&D for certain overseas clients.

"The Wuhan center may be new, but the team has already become a vital link in Autoliv's service network for China and the globe—and it is already delivering results," Mao said.

The facility even features a dedicated "Innovation Wall" where every patent earned by an engineer is displayed. The Wuhan team currently has seven patents pending.

Rapid Expansion: Deepening Roots in the Chinese Market

The Wuhan launch is no isolated incident. Since the start of the year, Autoliv has been equally aggressive in expanding capacity and forging partnerships.

In early January, Autoliv opened the second phase of its Jiading factory in Shanghai. With a total investment of 350 million yuan, the facility is designed to be a global benchmark for airbag production, further solidifying local smart manufacturing capabilities.

In mid-April, a joint venture between Autoliv and Hangsheng Electronics—Suzhou Hangsheng Autoliv Automotive Electronics Co., Ltd.—was officially inaugurated. Leveraging the strengths of both parents, the JV aims to deliver automotive safety electronic solutions tailored to the Chinese and global markets.

On August 10, Autoliv Wuhu Safety System Co., Ltd. broke ground in Wuhu's Jiujiang District. The new plant, featuring modern workshops and automated assembly lines, is slated to begin operations in 2027, providing high-reliability safety solutions to domestic and international OEMs.

Image Source: Autoliv

Customer partnerships are deepening in parallel. Beyond collaborations with companies like ChuNeng and XPENG, Autoliv signed a "Global Strategic Cooperation Framework Agreement" with Great Wall Motors on July 6, extending their partnership from local supply to global market coordination.

Building on this, Mao revealed that Autoliv will continue to deepen its domestic footprint and has already signed agreements for a new production base.

Against the current backdrop of many foreign Tier 1 suppliers retreating, why is Autoliv persisting with counter-cyclical expansion?

Mao points to confidence in the market as the core reason. China is the world's largest auto producer. Since annual output first surpassed 10 million units in 2009—making China the top producer and seller—the country has held the global sales crown for 17 consecutive years.

"It also comes down to the high level of trust our customers place in us," Mao added.

The numbers offer the most direct proof. In the second quarter, Autoliv's global net sales reached $2.803 billion, up 3.3% year-on-year, with sales in China growing by 3.4%.

More critical is the shift in client mix: Domestic brands accounted for 55% of Autoliv's China sales in Q2, with revenue from these brands jumping 44%. The growth was driven largely by the mass launch of new models from domestic players like Chery, Geely, and NIO.

Behind these figures lies Autoliv's strategy for hedging market volatility: rather than relying on a single client for growth, the company spreads risk by serving every customer well.

"If we can serve all Chinese clients effectively, then no matter which OEM ultimately wins the market, Autoliv will capture its share of the sales," Mao said.

Escorting Domestic Brands Global: Unlocking New Growth Avenues

Beyond deepening its presence in the local market, Autoliv is finding new growth opportunities in the globalization wave of Chinese domestic brands.

Data from the China Association of Automobile Manufacturers (CAAM) shows that China's auto exports reached 5.096 million units in the first half of 2026, a 65.3% year-on-year increase and the first time the half-year volume surpassed 5 million. Of this, new energy vehicle exports hit 2.355 million units, roughly 1.2 times higher than the previous year.

At this pace, full-year exports are poised to exceed 10 million units.

Amid this surge, Autoliv is actively positioning itself as an "escort" for domestic brands expanding overseas.

Image Source: Autoliv

According to Mao, Autoliv restructured its organization three years ago to keep pace with the rapid overseas expansion of domestic brands. It established two dedicated business lines: one for client engagement and another to gather customer requirements regarding development cycles, products, and pricing. This team coordinates with overseas groups in Thailand, Malaysia, Europe, and Brazil to respond to client needs with "one voice and one rhythm."

This year, Autoliv also created a dedicated engineering team for exports to oversee the implementation of global client projects.

Addressing the fact that R&D cycles overseas are typically slower than in China, Autoliv's Chinese team reportedly travels to various regions to help streamline and compress development processes.

"For export projects involving domestic brands, the decision-making authority lies primarily with the Chinese team," Mao noted. "We coordinate these projects, define the business models and management plans, and provide one-stop service to ensure rapid response. Then, we mobilize resources across regions to support on-the-ground implementation."

In her view, serving Chinese brands globally requires excellence locally first. Only by proving capabilities at home can the company deliver the same—or better—service abroad, rather than waiting until clients have already expanded overseas to step in.

Looking ahead, Mao views the demand for safety as the greatest certainty. "And the sheer size of the Chinese market is another certainty," she added.

Yet, the pace of change in China's auto market is accelerating, and technology iterations are speeding up. This means market demands—including safety considerations—will become increasingly diverse and fluid.

"But we remain convinced that opportunities always outweigh crises. Challenges exist, but overcoming them is what leads to success. If the path were always flat, there would be no growth," Mao concluded.

Gasgoo Munich- Data shared by Cui Dongshu, a senior official at the China Passenger Car Association (CPCA), reveals a challenging first eight months of 2026 for China's auto sector. Production slipped 3% to 20.31 million units, while revenue edged up 2.9% to 7.01 trillion yuan. However, costs climbed 4% to 6.24 trillion yuan, squeezing profits down 16% to 253.4 billion yuan. The industry's profit margin fell to 3.6%, a slide from 4.1% for all of 2025 and 4.3% in 2024. August offered a reprieve: production hit 2.7 million units, sales revenue rose 4.2% to 928.1 billion yuan, and profit surged 24% to 37.1 billion yuan, lifting the monthly margin to 4%.

Image Credit: Cui Dongshu

Breaking down the economics per vehicle, average revenue across the supply chain hit 345,000 yuan from January through August — a 5.5% annual increase. Yet costs rose faster, up 6.7% to 307,000 yuan, driving average gross profit down 5.1% to just 12,000 yuan. The production mix continued to shift: new energy vehicle output climbed 11% to 10.59 million units, claiming a 52% share of the total, while internal combustion engine vehicle production fell 15% to 9.72 million. In August alone, NEV penetration reached 61%, while ICE output plunged 26%.

The sector is caught in a pincer movement between rising costs and sluggish demand. Upstream prices for memory chips, lithium carbonate, non-ferrous metals, and semiconductors continue to erode automakers' bottom lines. At the same time, a persistent price war at the retail level has crushed margins, creating a classic scenario of higher revenue but lower profit. While August's profit rebound was significant, it was largely driven by a temporary lull in promotional activity. Volatility in chip and metal prices, combined with ongoing price competition, remains the primary constraint on earnings recovery.

The contrast with other sectors is stark. The computer and communications industry saw profits soar 110%, while auto profits slumped 16%. The sector's profit margin of 3.6% trails the overall downstream average of 6.6%. The downward trend is clear: margins fell from 4.3% in 2024 to 4.1% in 2025, and now sit at 3.6% for the first eight months of 2026. Even though ICE production showed a slight uptick in August, the pressure on profitability remains immense, with the sector's efficiency lagging significantly behind other consumer goods.

Amid fierce competition, relying on price cuts to drive volume is no longer a viable path to profitability. The industry must pivot toward supply chain optimization and tighter cost controls, leveraging technology premiums to boost per-vehicle returns. If the current cycle of price cutting persists, overall earnings will remain under pressure. While local governments are aggressively pushing trade-in policies to unleash domestic demand, the drive for high-quality development in the auto sector continues to be battered by the dual shock of upstream costs and weak end-market demand.

Gasgoo Munich- On September 29, China FAW Group and Guangzhou Automobile Industry Group formally signed a strategic cooperation framework agreement, uniting two of the country's leading state-owned automakers in a new phase of collaboration. The move aligns with national calls for high-quality development in the auto sector and reflects a strategic decision by both companies based on market trends and their own growth trajectories.

Image source: China FAW

China's auto industry is currently navigating a critical transition from scale to strength, marked by deep structural adjustments. As industry leaders, FAW and GAC Industry each bring distinct strengths to the table—from vehicle manufacturing and brand building to market expansion, global operations, and indigenous technological innovation.

According to their official statements, the partnership will adhere to principles of being "market-oriented, compliant with laws, equal, mutually beneficial, and win-win." Anchored by asset and capital linkages and driven by technological innovation, the two sides aim to coordinate cross-regional industrial resources and jointly boost operational quality and efficiency.

Just days prior, listed entity GAC Group (601238.SH, 02238.HK) halted trading starting September 14. At the time, the company only disclosed plans to issue shares to purchase assets and raise supporting capital, withholding the identity of the acquisition target. It wasn't until September 28, when GAC Group released a restructuring plan on the Shanghai Stock Exchange, that the market confirmed the target: a 50% stake in FAW Toyota Motor Co.

The agreement was signed by GAC Industry, the controlling shareholder of GAC Group. This strategic cooperation at the group level is proceeding in tandem with the listed company's asset restructuring.

Both companies pledged to steadily implement the collaboration, aiming to create an innovative model for strategic coordination between a central state-owned enterprise and a local state-owned enterprise. The goal is to build momentum for the high-quality development of China's automotive industry.

Gasgoo Munich- At a Beijing press conference for the 2026 World Intelligent Connected Vehicle Conference, Hao Lishun, deputy director of the equipment industry division at the Ministry of Industry and Information Technology (MIIT), outlined a three-pronged strategy. Anchored in the 15th Five-Year Plan for the intelligent connected new-energy vehicle sector, the ministry will push for deeper international cooperation across supply chains, standards and regulations, and corporate expansion overseas.

Hao Lishun. Image credit: 2026 World Intelligent Connected Vehicle Conference

Hao noted that the global auto industry is undergoing a profound shift. Vehicles are evolving from mere transport tools into smart mobile terminals, green storage units, and digital living spaces. International cooperation, accordingly, is reaching beyond traditional product trade to encompass joint R&D, collaborative manufacturing, shared supply chains, and regulatory synergy.

On supply chains, MIIT will champion global collaboration and cross-sector integration. The ministry will back foreign firms deepening their foothold in China — tapping its complete industrial base and mega-market to share in the growth. At the same time, it will steer domestic companies to absorb international best practices, sharpen their own innovation, and take Chinese technology and brands global.

On standards and regulations, China is already active in global rule-making through the UN World Forum for Harmonization of Vehicle Regulations (WP.29), the ISO, and the IEC. Going forward, the country will lean on multilateral and bilateral mechanisms to hardwire more of its technological breakthroughs into international standards and rules.

On corporate internationalization, Chinese vehicles now reach over 200 countries and regions, with domestic firms investing in vehicle and parts manufacturing across more than 80 overseas markets. Under the 15th Five-Year Plan, Beijing will shore up cross-border logistics, investment, and financing support. It will also tighten overseas risk controls and compliance frameworks, guiding companies to expand abroad steadily and methodically.

As for the conference itself, Hao said the 2026 edition will keep fostering dialogue, matching industry players, and deepening global coordination. It will set up standing exchange mechanisms in key areas — regulatory synergy, road-testing demonstrations, automotive data management, and V2X technology — to help build an open, collaborative global industry ecosystem.

The 2026 World Intelligent Connected Vehicle Conference is scheduled for Oct. 21–23 in Beijing’s Yizhuang district, under the theme “Gathering Intelligence, Unlimited Connectivity — Stepping Steadily Into the Era of Autonomous Driving.”