When Giants Tremble: How GenAI Could Disrupt Even the Most Digitally Mature Companies
This semester, I had the privilege of participating in a seminar led by Prof. Gianfranco Walsh, where I served as part of the jury evaluating student presentations on digital business models. Their task was to analyze existing business models (e.g., using the Business Model Canvas method) and to develop ideas for improved models. Each team received well-founded feedback on their ideas from experts. The following individuals participated as experts: Stefan Esselborn (VILSA-BRUNNEN Otto Rodekohr GmbH), Frank Bachmann (gürtlerbachmann GmbH, Hamburg), Dr. Ulrich Förster (Head of Siemens Foundational Technologies Development, Siemens AG), Prof. Mario Schaarschmidt (University of Duisburg-Essen), Prof. Klaus-Peter Wiedmann, and me.
The students took a deep dive into five highly relevant companies—Netflix, Airbnb, Uber, Flaschenpost, and Denns Biomarkt—all of them already considered digitally savvy, agile, and innovation-driven.
But here’s what kept echoing in my mind after the session:
What if even these tech-forward companies are not safe?
What if GenAI becomes the most potent disruptor yet—not just for laggards, but for digital pioneers?
Let’s explore this idea company by company, and consider how GenAI could attack their very foundations.
Netflix: A Studio in Every Pocket?
Netflix is often held up as the model of digital transformation. From DVD rental to streaming, from content distributor to award-winning content producer—they’ve proven their ability to reinvent.
But here’s the vulnerability: content production is slow, expensive, and bottlenecked by human effort.
Now imagine a world where anyone with an idea can instantly become a director. Using tools like OpenAI’s Sora, a user could describe a scene or story, and within minutes generate a personalized short film or episodic series—tailored to mood, language, even personal memories.
This would be Netflix meets TikTok meets Midjourney, where creativity is democratized at scale. Audiences shift from passive consumers to active creators. And suddenly, the most compelling “shows” aren’t coming from Hollywood—but from the café down the street.
Attack vector: hyper-personalized, AI-generated entertainment that bypasses traditional production altogether.
Airbnb: Trust at Scale Through AI
Airbnb disrupted the hotel industry with its platform model. But as the market matured, so did its trust issues—damaged properties, fake listings, underwhelming experiences.
Here’s where GenAI shines. Imagine a fully automated onboarding process for hosts, where AI handles video interviews, scans web presence for reputation markers, and conducts virtual property inspections using uploaded media. Combine this with sensor-based guest monitoring (e.g., privacy-compliant LIDAR or acoustics) and smart previews like “average noise levels” or “internet speed ratings.”
Suddenly, trust becomes scalable, objective, and cheap. GenAI could solve what even human moderators struggle with—consistently ensuring quality.
Attack vector: restoring quality and trust to peer-to-peer marketplaces via scalable AI-powered validation.
Flaschenpost: The Last-Mile Could Go Autonomous
Flaschenpost is a beloved service in German cities—no more carrying heavy crates of drinks up stairs. But they’re largely confined to urban centers with high density and flexible labor.
What if GenAI unlocked their growth into rural areas?
- Autonomous cars could do nighttime deliveries.
- AI-powered logistics could dynamically reroute based on weather, traffic, and energy prices.
- Your own car could become a revenue stream—offering it to Flaschenpost for AI-optimized delivery during idle hours.
- Drones (already a reality in China) could handle lightweight orders in remote towns.
Attack vector: removing the urban labor bottleneck through AI-driven logistics and autonomous delivery systems.
Denns Biomarkt: Organic Food Goes Hyperlocal
Denns has built a brand around organic and sustainable grocery shopping, but like all perishables, their inventory faces high spoilage risk.
Now, imagine AI-managed vending stations spread across city blocks—smart fridges that automatically restock based on sales data, weather patterns, and nearby events. These could be refilled by local farmers through an Uber-style dashboard, letting them sell directly at a premium.
This micro-distribution system would combine:
- AI forecasting (for inventory)
- IoT vending (for availability)
- Local fulfillment (for freshness)
Attack vector: disintermediating supermarkets with smart, AI-managed organic micro-markets run by local producers.
Uber: What If the Cars Worked Smarter Than the Company?
Uber transformed mobility—but even it has inefficiencies. Around 35% of its rides are deadhead trips (i.e., with no passenger).
Now imagine turning those trips into data-collection missions: recording emissions, noise levels, or mobile network strength. Uber becomes not just a mobility platform, but a data infrastructure company, selling environmental data to real estate agents, municipalities, and insurers.
Better yet, what if you eliminated the driver altogether? Yes, Uber is working on autonomy—but GenAI could accelerate fleet intelligence, optimize ride-pairing, and route vehicles in real-time based on urban dynamics.
Attack vector: monetizing inefficiencies through data, and ultimately, cutting out the driver entirely.
A New Era of Attack Vectors
The seminar was a wonderfully inspiring event, and I thank all the students for their sharp thinking, creativity, and real-world analysis. But it also left me with a haunting realization:
GenAI is not just another tool—it’s a potential system-level disruptor.
Even the most digital-native companies can be caught off guard if they fail to anticipate what’s coming next.
My Final Thoughts
What fascinated me most after the seminar wasn’t just how sharp and data-driven the student analyses were—it was the question that lingered in my own mind afterward:
How vulnerable are even the most advanced digital players in the age of GenAI?
Netflix, Uber, Airbnb—these aren’t laggards. They are the digital revolution. But GenAI doesn’t respect the old rules. It doesn’t just optimize processes—it reshapes what’s even considered a “business.”
- What happens when storytelling is democratized and scalable?
- When trust is built by algorithms, not humans?
- When logistics don’t need people, and distribution doesn’t need stores?
These aren’t edge cases. They’re emerging realities.
The power of GenAI lies in its ability to flip models upside down, lowering the cost of experimentation, reducing friction, and inviting millions of new "competitors" into markets previously controlled by a few platforms.
It’s not just about digital transformation anymore. It’s about disruption of the disruptors.
To all the students involved in the seminar: thank you for the insight and inspiration. You didn’t just map current business models—you helped us glimpse the new ones forming on the edge of imagination.
And that’s exactly where GenAI lives.