Welcome to a year full of jubilees: 140 years ago marked the dawn of the automobile, and today the Automobile-Elektronik Kongress proudly celebrates its thirtieth anniversary.

The keynote outlines how modern vehicle electronics and software have evolved and accelerated innovation, increased speed, and reshaped industry collaboration. It highlights the shift towards software-defined vehicles and AI with continuous updates and scalable software. It sets the stage for a forward‑looking discussion on customer‑focused innovation, partnering models, and the next chapter of automotive electronics.

The industry has spent years talking about SDVs, but how do we get going? In his keynote, NXP CTO Lars Reger will show what is possible with the silicon that’s available today. He’ll explain how vehicle architectures are shifting, introduce the “rolling skateboard” as a simple and memorable way to think about a car’s foundation, and highlight the practical building blocks—like zonal ECUs, intelligent gateways, efficient networks and safety‑focused power systems—that carmakers can use right now. Expect humor, real engineering insight, and a grounded look at how to move from buzzwords to buildable reality.

We witness the transformation of the automotive electronics value chain from a stable, global, technology-driven system toward a complex, fragmented, and regulatory-driven landscape. Historically, the industry relied on three core assumptions—declining semiconductor costs, global market integration, and software-led differentiation. Today, all three are weakening: geopolitics is reshaping supply chains, Moore’s Law no longer delivers cost reductions, and artificial intelligence is shifting value creation from software development to data and architecture.

Against this backdrop, BMW’s purchasing and supplier network manages a highly complex global ecosystem, ensuring resilience and scalability while handling significant volumes and dependencies. The company’s strategy emphasizes balancing global scale efficiencies with regional requirements and regulatory constraints.

BMW builds on established strengths such as innovation, system optimization, and cost discipline, while introducing new value drivers: standardization, data ecosystems, and resilient supply chain design. Future competitiveness will depend on ecosystem collaboration, technological sovereignty, and the ability to manage complexity under increasing uncertainty.

The automotive industry is undergoing a profound transformation, driven by pervasive AI. AI is rapidly becoming the new user interface, fundamentally reshaping how drivers and passengers interact with their vehicles and expect deeply personalized experiences. This session presents Qualcomm's visionary perspective on architecting resilient, future-proof Electrical Engineering (EE) platforms essential for unlocking disruptive, AI-driven innovation across the automotive domain.

 Nakul will discuss how the idea of ‘AI Everywhere’—powered by robust central compute—empowers OEMs to deliver truly customer-centric, agentic AI experiences that redefine driver interaction and vehicle functionality. This involves not just advanced in-cabin systems and automated driving, leveraging AI directly withing the vehicle, but also how the vehicle seamlessly integrates with its environment to enable contextually relevant experiences in real-time. The discussion will focus on strategic architectural principles and the industry-wide enablement required to scale AI software across diverse automotive applications, providing a blueprint for the next generation of intelligent mobility.

 The full potential of AI in automotive is still largely underestimated, and this talk will illuminate the foundational strategies for realizing that transformative future.

Ned Curic outlines how Stellantis is transforming the in vehicle experience by making technology simpler, more personal, and built around real human needs. At the core are STLA Brain and STLA SmartCockpit: two scalable, global platforms that unify software and electronics, reduce complexity, and enable continuous improvement. Together, they create a modern digital foundation that delivers intuitive, personalized experiences for customers while supporting efficient, scalable deployment across brands and markets.

Two years after the automotive industry faced a "now or never" decision, ETAS and BMW present what "now" means. At a time when the industry is confronted with countless initiatives surrounding the Software-Defined Vehicle (SDV), this presentation provides the decisive proof: The time for talk is over; the moment for delivery has arrived.

Learn how the industry's leading players are making the leap from PowerPoint slides and letters of intent to a real, functional, and scalable software solution. This is not just another presentation about SDV; it is a demonstration of implemented strategy, genuine collaboration, and tangible progress.

What you will take away from this presentation:
This presentation offers more than just a vision. It provides concrete insights into a working model and a clear roadmap for the future of automotive software development.

 The presentation includes:

• Tangible evidence:
  See how a new, collaborative "code-first" model replaces traditional, months-long approval processes and focuses on productive code and architecture meetings to dramatically accelerate development.
   
• A clear roadmap:
  We'll show S-CORE's evolutionary path from an open-source project to a production-ready, certifiable product. See the detailed release plan leading to a start of production (SOP) in 2028.
   
• An industry blueprint:
  Get a template for how the entire industry can stop reinventing the wheel with non-differentiating, basic software and instead focus resources on true innovation and unique customer experiences.

From Community to Product: A Clear Delivery Model
We will demonstrate the clear and pragmatic path from a collaboratively developed open-source core to a hardened, ETAS-supported, and production-ready product.

 Join us as we prove that the moment of delivery has arrived.

The automotive industry faces rapidly increasing compute demands driven by AI—from perception networks to large language and vision models—while silicon scaling slows. At the same time, software-defined vehicle (SDV) architectures and evolving user expectations require platforms that scale across vehicle lines while preserving software reuse and time to market. This exposes the limits of monolithic SoCs, where power, die size, and cost no longer scale efficiently.

Chiplet-based architectures are emerging as a structural solution. Already established in data center and consumer markets, chiplets introduce modularity, enabling the combination of different process nodes, targeted accelerators, and scalable compute elements without redesigning entire SoCs.

In automotive, chiplets enable heterogeneous and homogeneous scaling, cost-efficient silicon partitioning, and hardware evolution aligned with software lifecycles. However, they must meet strict requirements for functional safety, reliability, security, and long-term interoperability. Standardization—such as UCIe for die-to-die interconnects and emerging protocol frameworks—is therefore essential to enable a robust multi-vendor ecosystem, supported by industry initiatives like imec and ASRA.

This presentation highlights market trends, key challenges of chiplet adoption in automotive compute, and industry progress toward standardization. It also outlines Renesas’ R-Car Gen5 approach, combining high-performance monolithic compute with optional chiplet extensions under a unified software model, enabling scalable, future-proof vehicle platforms for the AI-driven era.

Today’s wiring harnesses are vehicle-specific products with an extreme level of complexity—up to 10³⁰ possible variants. Their production remains highly labor-intensive: approximately 1,500 employees are required, with only ~10% automation, and installation in the vehicle takes around 1 hour and 30 minutes. This model limits scalability, flexibility, and cost efficiency for both Tier 1 and OEMs.

Zonal architecture represents a structural enabler for a new supply chain and significant harness simplification. Since 2019, we have conducted multiple co-design initiatives with key customers and will introduce first automated harness solutions for German and U.S. OEMs in 2026 and 2027. However, current industrialization levels remain insufficient for large-scale automation rollout.

Through our cooperation with Luxshare, we have gained access as system partner to disruptive OEMs in China and California. These players combine in-house electronics and software development, shorter decision cycles, and sprint-based execution—while maintaining structured engineering processes—and consistently target fully automated vehicle assembly by 2030.

To unlock full potential, zonal architecture must align with production modules to optimize total cost of ownership, including assembly time and cost. This requires decentralized features, a robust real-time Ethernet backbone, and redistribution of software monoliths—while acknowledging that current IC readiness in safety, cybersecurity and reliability remains a constraint.

Our approach is to shift the focus of the ecosystem beyond pure SDV alone towards holistic total cost optimization.

The automotive industry is transitioning from hardware‑centric engineering to data‑driven, software‑defined value creation. The Industrial AI Cloud accelerates this shift by combining NVIDIA‑powered high‑performance computing with sovereign data architectures, low‑latency connectivity, and an integrated toolchain spanning development, validation, production, and fleet operations. Purpose‑built for industrial workloads, it scales AI across the entire lifecycle—from model training and large‑scale simulation to virtual validation, ADAS/AD development, and generative engineering—reducing development cycles from years to months through elastic burst compute.

Unlike generic hyperscale platforms, the Industrial AI Cloud provides controlled and compliant data spaces for European OEMs and suppliers, compute environments tailored to complex simulation workloads, and predictable performance close to the edge. It is natively embedded into open data ecosystems and relies on interoperable and sovereign standards to ensure transparency and vendor independence. Strategic partnerships with simulation specialists and leading open‑source initiatives—such as Eclipse SDV—extend this foundation across the value chain, enabling secure industrial AI applications, automated compliance, and continuous software innovation at fleet scale.

Connectivity plays a central for the Software‑Defined Vehicle. Seamless connectivity between edge, vehicle, mobile devices, and cloud backends enable reliable over‑the‑air updates, real‑time data services, digital twins, and a unified user experience across all touchpoints. Combined with end‑to‑end security, lifecycle‑wide data governance, and developer‑friendly processes, the Industrial AI Cloud transforms autonomous vehicles into data factories—unlocking continuous learning, rapid iteration, and sovereign operations as strategic advantages.

The Brain: The Next Frontier in Vehicle Intelligence
From Driver Monitoring to Driver Understanding

As vehicles become increasingly software-defined, connected, and automated, the automotive industry is shifting toward a more human-centric approach to mobility. Tomorrow’s intelligent vehicles will not simply monitor drivers; they will understand them. Yet today’s in-cabin sensing technologies remain largely limited to observing outward behaviors through cameras and surface-level interactions. Critical driver states such as cognitive distraction, fatigue onset, impairment, stress, and overload often emerge internally long before they become externally visible.

This presentation explores a new category of in-vehicle sensing: contactless neurotechnology. Neumo has developed the world’s first non-contact brainwave sensing system designed specifically for automotive applications. Embedded discreetly into the vehicle headrest, the NeuroBioMonitor (NBM) measures brain activity passively and without wearables, enabling real-time insight into driver cognitive state and condition.

The session will examine why EEG-derived signals have long been considered the gold standard for measuring fatigue and cognitive state, and why recent advances in AI, signal processing, and sensor design are now making neuro-based sensing practical for real-world vehicles. Attendees will see validation data from independent university testing demonstrating earlier detection of drowsiness compared with camera-based systems, along with discussion of broader applications including cognitive distraction, impairment detection, Level 3 handoff readiness, health and wellness features, adaptive HMI, and personalized in-cabin experiences.

Beyond safety, the presentation will discuss how deeper driver understanding may fundamentally reshape the relationship between humans and vehicles, enabling cars that adapt intelligently to occupants, reduce stress, improve comfort, and create more responsive mobility experiences.

The future cockpit will not only see the driver. It will understand the human inside.
 

LiDAR 2.0

Lidar 1.0 was all about the technology and the art of the possible. Lidar would play a key role in enabling compelling autonomous features and user experiences which would drive high levels of adoption, leading to affordable system costs ... this has simply not happened.

Lidar 2.0 is about value. While lidar remains a critical element in autonomous and semi-autonomous systems, Lidar 2.0 is focused on delivering the required performance at a cost level that enables unlocking value for both the OEM and the end consumer. This is the path to scale and mass adoption.

Glen DeVos will share his perspective on what this means for the Lidar industry and the developments that are required to enable Lidar to achieve mass adoption within the automotive industry.

For decades, the automotive industry has optimised how it builds software; scaling teams and refining processes to manage increasing complexity. Today, that model is being reset. As AI reshapes how software is conceived, built, and operated, the cost-per-feature is collapsing, unlocking a fundamentally new set of engineering and economic dynamics. 

In this keynote, Dominik Wee explores how recent advances in agent-assisted development, spec-driven engineering, and compressed lifecycles are transforming software from a linear process into a continuous, intelligent system. Domain experts are becoming builders, development cycles are shrinking from months to days, and quality, traceability, and compliance are increasingly generated as part of the flow. 

He will argue that automotive is uniquely positioned to lead this transition. The industry’s deep heritage in specification-driven development and safety engineering becomes a structural advantage in an AI-native world, enabling OEMs to combine rigorous certification with software-level speed. 

The session concludes by exploring how these shifts enable a new generation of vehicles; defined by continuous improvement, dynamic personalisation, and software that evolves with the customer over time. 

The automotive industry is leaving the era of the Software-Defined Vehicle and entering the age of the AI-Defined Vehicle (AIDV).

In this new paradigm, competitive advantage is no longer determined by mechanical excellence or isolated software features—but by data ownership, AI capability, and organizational intelligence.

AI-Defined Vehicles are built on centralized compute, service-oriented architectures, and continuous learning loops. They evolve after SOP. They improve through data. They monetize across the lifecycle. And they demand organizations that are as adaptive as the systems they create.

• Software-Defined & AI-Driven Vehicles: Centralized data and compute architectures power OTA updates, digital twins, and continuous AI-enabled feature deployment.
• Development: AI-native engineering will replace document-driven V-cycles as the primary innovation engine.
• Resilience in geopolitically unstable and cyber-threatened environments requires adaptive, Data and AI-driven decision systems.
• Culture and technology transformation will determine who succeeds. Cross-domain teams, empowered engineers, and real-time data transparency are now strategic imperatives.
• Intelligent Cockpits & Mobility Ecosystems as a data-driven, personalized control hub connected into a larger digital ecosystem, redefining safety, user experience, and revenue models.
• Success and Failure Stories with agile, data-driven OEMs and suppliers set the pace while laggards suffer setbacks. 

The AI-Defined Vehicle is not a feature upgrade. It is a structural shift in architecture, business model, and leadership/organization mindset.

The question is simple:
Will we build vehicles defined by data and AI —or supply parts to those who do?