The 2026 CES made clear that in-vehicle AI is evolving from voice assistants into physical AI companions capable of contextual awareness and proactive reasoning. This development also highlights the continued momentum behind Software-Defined Vehicles (SDVs), with the market expected to reach US$470 billion in 2026 and expand at a compound annual growth rate (CAGR) of 7% to US$1.19 trillion by 2036. 

AI is at the forefront of this transformation, underpinned by automotive semiconductors, including cockpit chips integrated through advanced packaging technologies to support the computational demands of increasingly complex scenarios. Amid this paradigm shift, Taiwan's supply chain is actively forging partnerships with global automakers and cross-industry players, transitioning from its traditional role as a consumer electronics manufacturing base into a technology powerhouse at the core of the smart mobility industry. 

Agentic AI Reshapes the Mobility Experience 

2026 is widely regarded as a watershed year in the evolution of in-vehicle AI, marking the transition from Generative AI to Agentic AI. If Generative AI is an expert at conversation and content creation, Agentic AI functions as a goal-oriented executor capable of proactively decomposing complex tasks and leveraging external tools. In mobility scenarios, Agentic AI is expected to become a physical companion capable of understanding a driver's implicit needs and taking action on the driver's behalf. 

As Agentic AI continues to evolve, multi-agent orchestration will emerge as a key use case. For example, if a driver tells the in-vehicle AI, "I want to have dinner with my family tonight," the system could initiate a series of tasks: automatically identifying restaurants that fit the budget, checking parking availability, making a reservation, and sending calendar invitations to family members. This represents a shift from executing a single instruction to handling multi-step decision-making. It also reflects the ambitions demonstrated at CES 2026 by automakers and technology companies such as Mercedes-Benz, BMW, and Bosch, which are working to move AI beyond functional operations toward intent understanding, fundamentally redefining the mobility experience. 

As vehicles become capable of intelligent decision-making, external sensing technologies must evolve in parallel—including the visual perception of cameras, the penetration capabilities of radar, and the spatial awareness of LiDAR. One emerging technology is 4D Imaging Radar, which adds vertical height (elevation) information to conventional three-dimensional data while accounting for the effects of adverse weather conditions. This makes it an increasingly important sensor for L2+ and L3 automated driving in complex environments. 

Another emerging technology is heterogeneous sensor fusion, which integrates data from cameras, radar—including 4D Imaging Radar—and LiDAR to construct an environmental perception model capable of operating accurately across varying lighting and weather conditions. AI algorithms cross-validate data from different sensing sources: cameras provide semantic recognition such as lane markings and traffic signals; LiDAR accurately maps three-dimensional environments; and radar maintains sensing capabilities in adverse weather. Together, these technologies create a safety redundancy mechanism in which different sensors serve as mutual backups, providing the decision-making confidence required for L3+ automated driving and enabling vehicles to interpret complex traffic environments more like humans. 

Next-Generation Semiconductors Address the Computing Bottleneck 

As vehicles evolve into mobile AI computers, two fundamental challenges must be addressed: computational power and energy efficiency. In the area of power management, electric vehicle voltage architectures are transitioning from the traditional 400V platform to an 800V architecture to enable ultra-fast charging. This transition is, in turn, driving demand for third-generation semiconductors such as silicon carbide (SiC) and gallium nitride (GaN). 

With its high-temperature and high-voltage tolerance, SiC is a critical component in traction inverters, helping significantly improve driving range and charging efficiency. GaN, meanwhile, benefits from its high-frequency switching capabilities and is expanding from consumer electronics applications into onboard chargers (OBCs), where it can substantially reduce module size and weight. 

In the computing domain, the massive processing requirements of L3+ automated driving and Agentic AI—including more than 1,000 TOPS for L4-level systems—are driving automotive electrical/electronic architectures (EEAs) away from distributed designs toward centralized zonal architectures. Rather than having control logic distributed across hundreds of ECUs throughout the vehicle, computing capabilities are increasingly being consolidated into a centralized "super brain" responsible for complex logic, AI inference, and decision-making. This enables software to be orchestrated on a unified platform without being constrained by the performance limitations of fragmented hardware. 

Building this automotive "super brain," however, is no easy task. As Moore's Law slows, simply shrinking process nodes is no longer sufficient to meet the stringent performance and power-efficiency requirements of in-vehicle AI. Advanced packaging has therefore emerged as a critical path forward. Chiplet architectures and heterogeneous integration technologies such as CoWoS (Chip-on-Wafer-on-Substrate) can integrate logic chips with High Bandwidth Memory (HBM) through 2.5D or 3D stacking. This architecture can overcome the traditional "memory wall" faced by monolithic chips while reducing data-transfer latency and power consumption, making it a critical foundation for high-performance AI computing.

This wave of technological innovation is also driving strategic alliances across industries. A notable example is the partnership between MediaTek and NVIDIA. MediaTek leverages Chiplet interconnect technology to integrate NVIDIA GPU cores into the Dimensity Auto platform, which is designed specifically for automotive applications. The collaboration combines MediaTek's strengths in low-power SoCs with NVIDIA's capabilities in AI and graphics computing to create an automotive-grade AI superchip, underscoring the growing importance of semiconductors in the future automotive supply chain. 

Taiwan's Supply Chain Actively Builds Global Partnerships 

The wave of cross-industry collaboration is not limited to chip design; it is sweeping across Taiwan's broader supply chain. As the SDV trend becomes increasingly established, Taiwanese companies are moving beyond their traditional role as hardware manufacturers. Through acquisitions and partnerships, they are actively collaborating with global automakers and Tier 1 suppliers in areas including AI computing, smart cockpits, cybersecurity, and energy management, positioning themselves as indispensable technology partners. 

In the smart cockpit segment, AUO, one of Taiwan's two leading display manufacturers, strengthened its capabilities in integrating human-machine interfaces (HMI) and climate-control systems through its acquisition of German supplier BHTC. CarUX, a subsidiary of Innolux, partnered with Pioneer to showcase next-generation cockpit solutions combining AI computing and Micro LED technology at CES 2026, demonstrating the ability of Taiwanese companies to help define the future mobility experience. 

In sensing and automated driving, Taiwanese companies are actively joining international ecosystems. oToBrite, for example, has entered NVIDIA's supply chain and is working with nearly 10 Taiwanese partners to develop automotive-grade camera modules based on the GMSL interface, targeting vision-AI applications for commercial vehicles and autonomous mobile robots. TMYTEK has partnered with the    HCMF Group    and related partners to introduce millimeter-wave radar technology into smart door systems, addressing use cases such as door-opening collision prevention and child presence detection (CPD) inside vehicles. 

System integration and cybersecurity also represent significant opportunities for Taiwanese companies. Foxconn is advancing the MIH Open EV Alliance and deepening its collaboration with NVIDIA, with plans to introduce an 800V architecture and AI factory infrastructure in Kaohsiung. In connected-vehicle cybersecurity, VicOne, a subsidiary of Trend Micro, has partnered with Tesla and charging infrastructure leader Alpitronic to advance the Pwn2Own Automotive competition and establish a cybersecurity framework for Software-Defined Vehicles. 

Table 1. Selected examples of Taiwanese companies entering the global automotive supply chain. Source: Compiled by the author based on publicly available information and industry developments. 

The value structure of the global automotive supply chain is undergoing a fundamental transformation. With its comprehensive semiconductor ecosystem and ICT supply chain, Taiwan is positioned as a critical technology "arsenal" supporting this mobility revolution. Against this backdrop, Taiwanese companies can consider three transformation priorities. 

First, move from manufacturing to defining specifications. Taiwan has traditionally excelled at manufacturing products according to customer specifications. In the AI era, however, chip architectures and sensing logic increasingly determine the performance of a vehicle's "nervous system." Taiwanese companies should take a more proactive role in defining underlying architectures and leverage advanced packaging and system-integration capabilities to help automakers address computing and energy-consumption challenges. 

Second, move from point solutions to system-level offerings. Future revenue models are expected to shift from selling individual hardware components toward providing integrated solutions. Taiwanese companies can leverage their existing hardware strengths to deliver integrated hardware-software subsystems, thereby increasing value-added content and strengthening long-term engagement with automakers. 

Finally, build a trusted and resilient supply chain. In response to geopolitical developments and the growing emphasis on data sovereignty, Taiwanese companies—as part of the democratic supply-chain ecosystem—can strengthen their global footprint and compliance certifications, positioning themselves as long-term partners for international automakers seeking to diversify and de-risk their supply chains.   In summary, 2026 is poised to be a year of value transformation for Taiwan's mobility industry. By continuously strengthening both software and hardware capabilities and deepening international partnerships, Taiwanese companies can evolve from component suppliers in automotive manufacturing into key participants shaping the future of mobility. 

Images and Article Source: Business Next (數位時代), “A Paradigm Shift in Mobility: Agentic AI and Next-Generation Automotive Semiconductors Open a New Chapter.” 

Content Source: Taiwan External Trade Development Council (TAITRA).