The discussion opened with a critical assessment of where European investors should focus their AI bets, with Yariv Adan immediately highlighting the industry's most pressing challenge.

Adan warns of what he terms "commoditized magic" - the phenomenon where breakthrough innovations become open-source within 24 hours. « The time between creating a new state of the art thing and the open source version of it now is about 24 hours », he observed, fundamentally reshaping investment strategy requirements.

This commoditization risk drives Adan toward investments with two key characteristics: unique data that cannot be easily scraped or generated, and specialized expertise that cannot be readily simulated. He sees Europe's dense academic and industrial expertise as a competitive advantage, noting « Europe, with its dense, strong academic and industrial expertise actually has a good shot at it ».

Olivier Schuepbach reinforced the urgency of rapid scaling, emphasizing that slow business models face immediate competitive pressure. « If you're waiting or have a business model which is not scaling quick enough, I mean you get very much competition and the barriers to entry are no more there », he explained.

Schuepbach highlighted a fundamental shift from previous technology waves: « It's not only the product which is being totally revolutionized with AI but as well the way of doing it and the how to do it ». This extends beyond product development to encompass entire company-building methodologies, creating an acceleration imperative for startups.

Tech-Bio: Europe's Defensible AI Frontier

Julien Pache identified biotechnology as a particularly promising intersection for European AI investment. The tech-bio sector combines scarce, specialized data with deep domain expertise - creating natural barriers against commoditization.

« You have data that is hard to find, quite scarce, quite specialized, that is hard to generate and obviously the capability now and expertise from people that understands the problem or the drug development pipeline in a very specific way », Pache explained. He sees Europe's large pharmaceutical companies and specialized talent pools as fundamental advantages in this space.

The reference to DeepMind's AlphaFold and similar foundational efforts demonstrates how AI can revolutionize drug development pipelines, with Europe positioned to build defensible companies in this intersection of data scarcity and domain expertise.

Geopolitical Winds Reshaping European Tech Strategy

The panel identified significant geopolitical shifts creating new opportunities for European technology development. Schuepbach pointed to recent statements from US political leadership as a "wake-up call" for Europe to develop indigenous technologies rather than defaulting to American solutions.

« We have right now a huge opportunity », Schuepbach argued, citing Europe's talented workforce and emerging political will to « push its own technologies instead of subcontracting that elsewhere in the world ».

However, Adan cautioned against overly regional thinking, drawing from his Israeli experience: « Israel was never a market on the first day. You have sales and business development in the US ». He criticized some European startups for limiting themselves geographically, suggesting that while Europe can be an excellent place to build technology, founders must think globally for distribution and scaling.

Humanity's Resilience Challenge: An Alien Perspective

Philippe Van Caenegem offered a broader philosophical framework, positioning current AI developments within humanity's broader challenge of managing multiple exponential changes simultaneously. When asked to take an "alien civilization view" of humanity's current moment, he emphasized resilience as the crucial capability.

« We are going to live transformative years for various reasons. Climate change is coming up on us, we feel the tensions everywhere, geopolitical tensions, etc. And on top of it, there's this massive potential of unlocking this new technological step », Van Caenegem observed.

He sees intelligence commoditization as unprecedented in human history, comparing it to infrastructure developments like electricity but at an unprecedented scale. His investment thesis focuses on building resilience through better data utilization, particularly in agriculture and sustainability applications where satellite data and other information sources remain poorly integrated.

Adan echoed this optimistic view of AI's democratizing potential, highlighting education, healthcare, agriculture, and energy efficiency as areas where AI could address fundamental human needs. « I think we have an opportunity and I would just like to bring the very best education at PhD level to every person on the planet », he suggested, viewing AI as a tool for democratizing access to expertise and knowledge.

Investment Red Lines: What These VCs Won't Touch

The panelists were candid about their investment exclusions, revealing important market dynamics and ethical considerations.

Van Caenegem explicitly ruled out European LLM development, calling it too expensive and mature for startup investment. He also expressed concern about AI applications designed for user manipulation, particularly combining Meta's data assets with personalized AI influence capabilities.

Pache distinguished between descriptive and normative investment criteria. Descriptively, he avoids anything facing commoditization risk. Normatively, he excludes AI defense applications, though acknowledging this as a personal preference rather than a universal position.

Adan identified broad commoditization across the entire "gen AI stack," including connectors, identity, payments, and orchestration tools. His focus narrows to two areas: process-level automation requiring unique data, and specialized infrastructure components where smaller expert teams can outcompete larger organizations.

Schuepbach took a positive position on defense technology, arguing that European attitudes toward defense investment have shifted significantly. «  Europe has realized it needs its own defense », he stated, viewing defense as an opportunity rather than a taboo, particularly given recent geopolitical developments.

The Death of SaaS: A Heated Debate

The panel's most contentious discussion centered on whether traditional Software-as-a-Service models face extinction in an AI-driven world.

Adan argued for fundamental disruption, predicting a shift from complex, expensive, rigid software to ephemeral, hyper-contextual applications. « I think that in the future there will be no software that is built to last. It will be so easy to generate a specific software for the thing I actually need to do right now », he explained, comparing future software creation to disposable napkins - created for immediate use and discarded afterward.

Van Caenegem offered a more nuanced view, distinguishing between SaaS as a technology stack and as a distribution/financial model. « SaaS before anything else, it's a distribution model, it's a financial and distribution model», he argued, suggesting the underlying business model concepts will evolve rather than disappear entirely.

Schuepbach focused on the shift from destination-based to agent-based interactions. « We are now in a world where we're sending agents to hunt for us», he observed, predicting a significant impact on applications designed as destinations for specific user needs and putting pressure on SaaS/services to adapt.

The panel reached surprising consensus that traditional SaaS faces major disruption, though they disagreed on timeline and investment implications. When pressed for investment decisions, most panelists indicated they would not invest in next-generation SaaS/service applications, viewing the space as too crowded and likely to be dominated by existing platform players.

Alternative Investment Strategies in an AI-First World

Given somen of the panelists’ pessimism about traditional software investments, these panelists outlined alternative focus areas.

Pache described a marketplace strategy, investing in AI tools that serve as lead generation for service marketplaces rather than traditional subscription models. His approach involves deliberately commoditizing software to capture transaction value in professional services.

Van Caenegem emphasized data infrastructure and governance, particularly for European companies struggling with data management, legal compliance, and digital transformation. He sees patient capital models as better suited to supporting companies through extended transformation periods.

Adan maintained his focus on process automation with defensible data moats and specialized infrastructure components that can become horizontal platforms or attractive acquisition targets.

The Future of Venture Capital: Structural Transformation Ahead

The discussion concluded with a sobering assessment of venture capital's future in an AI-transformed economy.

Adan predicted potential industry obsolescence, arguing that an economy of much lower margins challenges fundamental VC assumptions. « If someone tells me that hey, in 10, 15 years there are no more ventures, I would not be surprised », he stated, advising founders to consider bootstrapping companies built for low-margin operation.

Schuepbach highlighted private equity's growing role as an alternative exit path, particularly important in Europe where IPO exits are still building momentum. This evolution provides new scaling paths for companies and exit opportunities for early stage investors.

Van Caenegem Spoke about the evident need for patient capital addressing the gap between traditional VC and private equity, designed for companies requiring longer development timelines.

Pache offered the most traditional view, arguing that while building costs decrease, distribution costs increase in competitive markets, maintaining the need for significant capital deployment. He predicted industry consolidation due to poor returns rather than fundamental model obsolescence.

The panel agreed that algorithmic investing might disrupt early-stage venture capital, though Pache argued that early-stage investment fundamentally concerns people and chemistry rather than data-driven decisions.

Key Takeaways for European AI Executives

1. Focus on Defensible Moats: Prioritize investments requiring unique data or specialized expertise that cannot be easily replicated or automated.

2. Speed is Critical: Commoditization timelines have compressed to hours rather than years, making rapid scaling essential for competitive survival.

3. Think Global from Day One: European companies must plan for global distribution despite building locally, avoiding regional market limitations.

4. Tech-Bio Offers Strong Opportunities: The intersection of biotechnology and AI provides natural defensibility through data scarcity and domain expertise.

5. Traditional SaaS Models Face Disruption: Expect fundamental changes in software distribution and pricing models as AI enables more personalized, ephemeral agentic applications.

6. VC Industry Set to Evolve in an AI world: Founders can evaluate investor alignment with new economic realities and complement with supplemental funding paths.

The Panoramai panel revealed a venture capital community grappling with fundamental shifts in technology economics while maintaining optimism about AI's potential to address humanity's greatest challenges. For European executives, the message is clear: move fast, build defensible positions, and prepare for a transformed technology landscape where traditional assumptions no longer apply.

No statements constitute investment advice or solicitation of funds. Readers should consult qualified financial advisors for investment decisions.