Sebastian Goebel is Subject Matter Expert in the CEIPI-EPO Master of IP Law and Management
Premium vehicle manufacturers have lost control of the in-car voice assistant interface to tech giants like Google, primarily due to superior technology, ecosystem integration, and a strong patent👉 A legal right granting exclusive control over an invention for a limited time. portfolio. This shift threatens OEMs’ brand👉 A distinctive identity that differentiates a product, service, or entity. identity, data ownership, and revenue streams. To avoid similar strategic missteps in future tech domains, companies must adopt proactive, use-case-driven IP development. Sebastian Goebel at the IP Business Academy shows best practice about expertise and tools needed to build AI-supported patent portfolios that secure long-term competitive advantage.
Here you can find Sebastian Goebel on the digital IP lexicon 🔗𝗱𝗜𝗣𝗹𝗲𝘅 on software patents, AI-generated inventions👉 An invention created autonomously or semi-autonomously by an AI system. and AI-supported patent drafting.
In the automotive world, prestige has long been associated with performance, engineering excellence, and luxury design. But in the digital era, a new battleground has emerged: intelligent voice assistants. Once considered a futuristic novelty👉 Requirement that an invention must be new and not previously disclosed., voice interaction is now a central pillar of the in-car experience. It’s not just about convenience anymore—it’s about control, brand identity, data, and value creation. And premium vehicle manufacturers have found themselves increasingly outmaneuvered in this high-stakes technological race.
This blog post dives into the evolution of voice assistants in premium vehicles, why automakers lost control of this critical interface to tech giants—particularly Google—and why their patent strategies failed to anticipate the shift. In the second part, we explore how companies can avoid repeating this mistake by adopting a structured, AI-supported patent development approach, as advocated by Sebastian Goebel, IP Subject Matter Expert at the IP Business Academy.
The Rise of Voice Assistants and the Strategic Setback for Premium Automakers
From Novelty to Necessity: How Voice Assistants Entered the Driver’s Seat
Voice recognition in vehicles started as a clunky, limited feature—often only able to control basic infotainment or navigation functions. Early iterations were proprietary, slow, and often required exact phrases. However, as consumer expectations evolved with the rise of smartphones and smart speakers, automakers were pressured to deliver a voice interface experience that matched or exceeded what users had come to expect from devices like Google Assistant, Amazon Alexa, and Apple Siri.
Voice assistants became more than a convenience—they were an interface to digital ecosystems and intelligent services, offering personalized content, real-time traffic updates, hands-free communication, and increasingly, AI-driven decision support. These capabilities required robust data handling, machine learning, and cloud integration—areas where Big Tech had already established deep expertise.
The OEM Dilemma: Why Premium Manufacturers Resisted Big Tech
Automakers have traditionally resisted third-party platforms for one main reason: control. Control over:
- Customer experience and brand identity: Allowing a Google Assistant into the car also meant allowing Google’s branding and user interface.
- Data ownership: Data from user interactions, driving habits, and infotainment preferences is immensely valuable—and OEMs didn’t want to share.
- Revenue streams: Automakers feared disintermediation, where tech platforms could monetize services that OEMs had planned to offer themselves.
Thus, many premium automakers attempted to build in-house solutions—BMW’s Intelligent Personal Assistant, Mercedes-Benz’s MBUX, or Audi’s MMI system. However, these offerings often paled in comparison to Big Tech’s assistants in terms of natural language processing, ecosystem integration, and user experience. Voice assistant capability became a dealbreaker for tech-savvy consumers.
Google’s Winning Formula: Capabilities, Ecosystem, and Patents
So how did Google win the voice assistant race in the car? Three core advantages created a perfect storm:
- Superior Technology
Google had a multi-year lead in AI-powered voice recognition and natural language understanding. Its assistant could:- Understand context and conversation history
- Access a wide array of cloud-based services
- Integrate deeply with user data from other Google services
- Support multiple languages and accents with high accuracy
No OEM could match this level of development on their own.
- Robust Ecosystem
Google’s ecosystem advantage cannot be overstated. The Assistant didn’t just understand voice—it connected seamlessly to Gmail, Google Maps, Calendar, YouTube, smart home devices, and Android smartphones. This made the Assistant not just functional but indispensable to users. - Patent Position
Most crucially, Google’s strong IP portfolio in voice recognition, AI, contextual computing, and cloud architecture created a defensive moat. Premium vehicle manufacturers found themselves boxed out of developing truly competitive solutions without licensing👉 Permission to use a right or asset granted by its owner. core patents or risking infringement👉 Unauthorized use or exploitation of IP rights.. This IP pressure nudged many toward Android Automotive OS, which comes bundled with Google Assistant.
Android Automotive has since made significant inroads, particularly among premium brands like Volvo, Polestar, and GM. Even once-reluctant OEMs have started to adopt it as a default option, because the cost of building a competitive alternative—from both a tech and IP perspective—is simply too high.
The Danger: Platform Dependency and Loss of Differentiation
By surrendering the voice interface to Google, automakers risk👉 The probability of adverse outcomes due to uncertainty in future events. repeating the mistake the PC industry made with Microsoft Windows: becoming commodity hardware providers while the software platform captures most of the user engagement, data, and margins.
This dependency raises several threats:
- Loss of brand identity:
The Google Assistant offers a uniform voice, tone, and interaction style across all vehicles, regardless of manufacturer. This homogenization makes it difficult for premium automakers to differentiate their digital in-car experience. As a result, users associate the intelligence of the system with Google, not the vehicle brand—diminishing the OEM’s emotional and experiential value. - Limited control over data:
When Google powers the voice assistant, the bulk of user interaction data—like voice commands, location history, and usage behaviour—is funnelled into Google’s servers. OEMs lose visibility into how drivers engage with their own systems. This hampers their ability to improve user experience, develop personalized services, or even innovate based on real-world usage. - Revenue dilution:
In-car voice assistants are a gateway to lucrative services such as e-commerce, digital subscriptions, and location-based advertising. When Google acts as the intermediary, it captures a significant portion of these revenue opportunities. Automakers are effectively handing over potential income streams to a third party while bearing the cost of hardware and integration.
OEMs are now in reactive mode. What began as an attempt to preserve control has backfired into a strategic surrender. The critical question is: how can manufacturers prevent similar losses in the next wave of innovation👉 Practical application of new ideas to create value.?
Strategic Positioning Through IP—Why Sebastian Goebel Offers a Path Forward
This is where a forward-thinking IP strategy👉 Approach to manage, protect, and leverage IP assets. becomes not just important but existential. The voice assistant saga shows what happens when innovation outpaces IP preparation. But there is a way to regain control and future-proof emerging technologies—AI-supported patent portfolio development tailored to real use cases.
The Need for Systematic, Early, Use-Case-Based IP Development
The solution is not simply filing more patents, but doing so earlier, strategically, and use-case-focused—before competitors define the standards and occupy key IP positions. This approach requires:
- Understanding emerging technology landscapes (like generative AI, connected mobility, or predictive maintenance):
To build a strong IP strategy, companies must first grasp where technological innovation is heading. This means closely monitoring trends such as generative AI, smart vehicle ecosystems, and data-driven maintenance solutions. A clear understanding of these evolving domains helps identify white spaces and anticipate where valuable patents can be positioned. - Mapping out user-centric use cases within these landscapes:
Once a technology landscape is understood, the next step is to define how it delivers value in real-world scenarios. This involves identifying specific use cases that solve user problems, enhance experiences, or increase operational efficiency. Grounding innovation in practical applications ensures that resulting patents are relevant, valuable, and strategically aligned with market needs. - Capturing inventions👉 A novel method, process or product that is original and useful. in a structured, repeatable way:
Innovation should not rely on chance or ad-hoc brainstorming. A systematic process—such as structured invention disclosure sessions or innovation workshops—ensures that ideas are consistently captured, documented, and refined. This repeatable approach builds a steady pipeline of high-quality inventions that can be translated into strong patent assets. - Leveraging AI tools for prior art search, invention evaluation, and drafting:
AI-powered tools can significantly accelerate and enhance key patent processes. They can quickly analyse large patent databases for novelty searches, assess technical relevance, and even assist in drafting claims and descriptions. Using these tools not only reduces time and cost but also improves the quality and competitiveness of the resulting patents.
This shift from reactive to proactive IP development requires a new kind of patent professional—one who understands AI, business strategy, and portfolio building. That’s precisely why the work of Sebastian Goebel, IP Subject Matter Expert at the IP Business Academy, is so timely and essential.
Why Sebastian Goebel is the Right Expert at the Right Time
Sebastian Goebel is uniquely positioned to help companies avoid the same trap premium vehicle manufacturers fell into. His work sits at the intersection of patent law, AI, and strategic portfolio management👉 Strategic management of diverse assets to optimize returns and balance risk.. Through his teaching, writing, and consulting, he empowers innovators to build strong, defendable patent portfolios early—long before their ideas reach the market.
Let’s break down what makes him the ideal guide in this domain:
- Expertise in AI and Patent Strategy
Goebel has been a leading voice on how generative AI can supercharge the patenting process. He’s authored guides like “How Can Patent Practitioners Profit From Generative AI”, providing hands-on insights into using tools like ChatGPT for:- Drafting claims and specifications
- Performing novelty assessments
- Identifying white spaces in technology fields
- A Teaching Approach Rooted in Practice
Through the IP Business Academy, Goebel delivers webinars and courses that aren’t abstract theory. They’re tailored for real-world application in corporations and startups alike.
Participants learn how to structure innovation workshops, extract invention disclosures from R&D teams, and convert those into strategic patents. His “Drafting Guidelines” are widely used by professionals seeking to raise the quality and impact of their patent filings.
- Strategic Focus on Use Cases
Goebel’s philosophy centers on use-case-driven patenting—identifying the real-world scenarios where new technology will create competitive advantage. This is particularly critical in emerging areas like autonomous driving, predictive diagnostics, or digital twins in mobility. It also avoids filing empty patents on vague concepts and instead builds strong positions around how the technology is actually applied.
- A Long-Term Vision
Goebel doesn’t just teach how to file a good patent—he helps companies build a portfolio strategy that supports their business objectives. His methods ensure that patent filings align with product roadmaps, licensing goals, and competitive positioning.
This kind of strategic foresight is precisely what the automotive industry lacked during the voice assistant transition—and what it must now regain to compete in the next wave of innovation.
Conclusion: Control Through Strategic IP
The story of voice assistants in premium vehicles is not just about technology—it’s about timing, patents, and control. Automakers hesitated, underinvested in AI capabilities, and lost the interface that connects users to the digital car experience. Now they face platform dependency, branding dilution, and lost data sovereignty.
But this outcome is not inevitable. With the right tools, frameworks, and expertise, companies can avoid such strategic defeats in future technology cycles.
By adopting AI-supported, use-case-driven IP development, and learning from experts like Sebastian Goebel, innovators can take back control—building portfolios that support long-term differentiation, defend market position, and unlock value from invention.
Because in the age of intelligent machines, the most important asset isn’t the car or the code—it’s the idea, and the right to own it.
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