China’s approach to AI in mobility is moving from concept to commercial scale, and Neusoft used ELIV 2026 in Baden-Baden to make that case to a global automotive audience. In a keynote at the International VDI Congress, Senior Vice President Angela Wang argued that China’s market is shifting from finding a scenario for a technology to a model where the scenario defines the technology. That message matters for investors because it points to a faster path from lab work to real-world deployment, especially in software-heavy industries where the winners will be those that can iterate quickly, integrate deeply, and scale across markets.
Wang’s central point was straightforward: China’s AI mobility market is no longer just adding features for the sake of it. Instead, companies are organizing product development around actual use cases, then building technology to fit those situations. In her words, the paradigm shift is moving from hunting for scenarios with ready-made technology to forging technology based on scenarios, and from feature stacking to experience-driven design. That is a useful frame for analysts because it ties innovation to adoption. The real advantage is not just better software, but a shorter path from engineering to commercial use.
The company’s argument is that China has the ingredients for this shift at scale. Wang said China’s complex and diverse traffic scenarios provide abundant, high-quality data for AI algorithm training and improvement. She also pointed to digitally native consumers who are receptive to new technologies and willing to pay for intelligent experiences. In practical terms, that means feedback loops can close faster in China than in many other markets. For mobility investors, that can translate into stronger product learning, quicker software updates, and a more powerful base for exportable automotive solutions.
The keynote also highlighted how AI is changing the cockpit and navigation experience itself. Wang used Neusoft OneCoreGo 7.0 as an example of how AI can communicate and interact like a human and reshape the user experience in navigation. She also cited NAGIC.AI as a case study showing how software architecture can be flexible enough to support both centralized and distributed approaches for new and legacy vehicles. That matters because the automotive transition is not happening in a clean slate environment. The market needs tools that can bridge old systems and new platforms while still improving the user experience.
The broader message for the global auto industry is that AI is becoming embedded in the vehicle experience rather than sitting on top of it as an add-on. ELIV itself reflected that trend, with major focus areas including AI, software-defined vehicles, automated driving, and cockpit and customer experience. Neusoft’s presentation fits neatly into that shift. If the cockpit becomes a digital space that understands context better, then the value pool moves toward software orchestration, interface design, and continuous improvement. That is exactly where China’s scale and speed can matter most.
Wang also stressed that user-facing AI is only half the story. Behind the scenes, AI is being used to reshape how software is developed, moving from human-defined processes to AI-generated ones in order to cover a growing number of scenarios. She also described a shift from real-vehicle testing toward digital twin simulation to accelerate iteration. For engineering teams, that suggests a more efficient development cycle and a better way to handle complexity. For investors, it signals that AI’s economic impact in mobility is not limited to the car cabin. It reaches into the software factory itself.
Neusoft’s own examples were meant to show that point in action. Wang said AI has already delivered significant efficiency gains across various stages of the software production lifecycle, and she pointed to the company’s One Furnace Enterprise-Grade AI Testing Solution as a case where AI digital employees have reshaped quality, cost, and delivery. Those are the metrics that matter in enterprise software and automotive software alike. If AI can improve the economics of testing and delivery, then scale becomes even more valuable, because each additional deployment can reinforce process efficiency rather than strain it.
Wang closed by saying the China market could offer valuable experience in AI implementation to the global automotive industry. She argued that closer collaboration across regional markets can accelerate large-scale AI deployment in mobility and deliver strong experiences to consumers worldwide. That is an important perspective for multinational OEMs and suppliers. China is not just a market to enter; it is increasingly a place where new operating models are tested, refined, and exported. In a software-defined auto era, that can make China a global reference point for product strategy.
This is also where Neusoft’s own global footprint becomes relevant. The company says it has 35 years of automotive software R&D and a global R&D and delivery network centered in China, Germany, the USA, Japan, and Malaysia. It says its automotive products and services have been integrated into 2,000+ vehicle models across 130+ countries and regions, serving 50+ global OEMs. Those are company claims, but they show why Neusoft is trying to position itself as a bridge between China’s AI deployment experience and the needs of international automakers. The scale is meaningful if customers want solutions that travel well across markets.
What makes the message at ELIV 2026 especially relevant is that it comes at a moment when the auto industry is rethinking the balance between hardware, software, and user experience. Neusoft’s presentation suggested that the strongest companies will be those that can orchestrate capabilities from wherever they emerge and build on diverse ecosystems around the world. That is a pragmatic view of global competition. It does not depend on one geography having all the answers. It depends on the ability to connect engineering strengths across borders and turn them into deployable products.
For China watchers, the takeaway is bullish. The country’s AI mobility ecosystem appears to be moving beyond experimentation and into a phase where scale, consumer openness, data richness, and fast iteration reinforce one another. Neusoft used ELIV 2026 to argue that this model can help shape the next stage of global automotive software. No market reaction was identified for the stock around the event, and no follow-on corporate milestone was specified. Even so, the strategic message is clear: China’s scenario-defined approach is becoming a template that global automakers will have to study closely.
