The Future for European AI Companies
European founders face both remarkable opportunities and some uncomfortable friction in the domain of artificial intelligence.
AI, understood by some as the biggest technological shift for business since the cloud, has the potential to reshape standard business processes — from corporate giants to Germany’s mittelstand.
For European founders and governments, the current challenge lies not just in understanding the shift but in adapting to it effectively to position Europe as a major AI player.
There are a few hurdles for European founders in AI, particularly around funding, talent acquisition, regulatory obstacles, and resource allocation. However, there’s also plenty of room for optimism.
Adoption and Market Readiness
For European industries, the adoption of emerging technologies has historically been slow. As Daniel Khachab, co-founder and CEO of Choco, observed in his interview on 20VC, adoption challenges often stem from entrenched workflows and the need for training.
While SaaS adoption has traditionally been hindered by onboarding complexities, AI and agent-based technologies offer a more intuitive interface, allowing users to communicate with machines like humans.
This potentially accelerates the adoption curve, as "there's nothing to learn," as Khachab points out, making AI particularly well-suited for traditional industries that have been resistant to digital transformation up to now.
However, there are notable barriers:
Implementation and Data Readiness: European companies, especially traditional businesses, struggle with implementing AI due to issues like data cleanliness and readiness. Though budgets are available, the lack of streamlined post-agreement processes poses an implementation bottleneck.
Data Security and Compliance: Large enterprises are wary of data risks associated with cloud-based AI solutions. Although on-premise options exist, ensuring data security within these AI solutions continues to be a significant hurdle.
Simplified integration processes that focus on user-friendly interfaces, combined with government-backed incentives for on-premise solutions, can accelerate adoption. Governments can support this by establishing AI-specific compliance standards that help de-risk adoption for traditional industries.
The Entrepreneurship Gap
Europe faces a considerable challenge in nurturing the talent required for foundational AI models. Building a competitive AI ecosystem demands not only capital but also a concentration of specialized talent.
Khachab aptly described the issue as structural, noting a talent gap that hinders Europe’s ability to compete with entities like OpenAI and Anthropic in the U.S. While Europe boasts resources in places like DeepMind and AI centers in Paris, attracting and retaining talent remains challenging.
On the funding front, European founders often face limited access to venture capital compared to their U.S. counterparts. Khachab also emphasized that the "quality of European founders is much worse than [in] the U.S.," citing structural issues that make it harder for the continent to produce ambitious, high-risk founders willing to build companies at the scale required for AI breakthroughs.
That’s not to say that there’s any shortage of potential, as Europe remains a hotbed for technical talent, just that the talent tends not to be directed towards entrepreneurship.
Addressing the talent gap requires a twofold approach:
Education and Training: Government-sponsored programs, coupled with cross-border mobility for AI talent, can ensure a stronger pipeline of skilled workers deciding to move into emerging technology entrepreneurship.
Targeted Funding: Funding must be directed toward established players and early-stage startups to nurture foundational AI models. Governments could establish dedicated funds or co-investment vehicles to stimulate investment in the AI space, prioritizing talent retention and high-risk, high-reward initiatives.
Chips and Energy
Europe’s lack of infrastructure in semiconductor production and affordable energy poses additional barriers. AI development demands vast computing resources, primarily GPUs, which require a robust semiconductor industry and stable energy supply.
Despite efforts by the German government to incentivize chip production, Khachab points out that funding has often been misallocated to companies like Intel instead of more relevant players like TSMC or Nvidia, which have experience in producing AI-specialised chips.
In light of Europe’s shift toward renewables, energy remains a costly concern. Chip manufacturers require significant energy resources, and energy costs can directly impact the scalability of European AI ventures.
Without affordable, reliable energy, founders will struggle to compete with U.S.-based companies with access to cheaper infrastructure. France is probably the best example of a European country taking the bull by the horns on energy policy to ensure the future of their nascent AI industry.
Governments need to:
Align Resources with Industry Needs: Directly incentivize GPU-specialised chip manufacturers like Taiwan Semiconductor and Nvidia rather than broad-based semiconductor companies.
Prioritise Affordable Energy Solutions: As Khachab suggested, nuclear energy remains a contentious but potentially viable option. Exploring solutions such as microgrids or renewable subsidies for energy-intensive sectors may offer a sustainable solution without compromising long-term environmental goals.
Jumping Regulatory Hurdles
Europe's regulatory landscape, while traditionally strong in consumer protection and data privacy, offers unique opportunities to establish a supportive foundation for AI growth.
Though slower to adapt than other regions, Europe has laid a foundation of trust that can be leveraged as a competitive advantage in the development of AI technologies. European founders often point to regulation as a challenge, yet it does not deter great entrepreneurs from building transformative companies.
As Daniel Khachab notes, regulatory hurdles are sometimes used as a "catch-all" excuse for slower development across the EU, but regulation doesn’t stop great founders from starting companies and finding a way to prosper.
However, there is definitely room for improvement. A harmonized AI framework across the EU, for example, would reduce the complexity of compliance and enable startups to navigate requirements with greater agility.
Fast-tracking regulatory approvals and developing AI-specific frameworks that balance data privacy with innovation can provide European startups with a supportive yet responsible policy environment.
Such an approach could position Europe as a leader in ethical AI, attracting founders who value both innovation and consumer trust—critical components for generationally impactful companies.
Navigating Fragmented Markets
One of the most cited challenges in scaling European tech startups is the fragmented market across the EU, with multiple languages, regulations, and consumer preferences.
This fragmentation often contrasts with the more unified U.S. market, where scaling a product nationally can feel less complex. European founders and investors frequently point to this as a barrier, particularly when launching regulated technologies that require compliance with diverse national frameworks.
Yet, as demonstrated by successful companies like Revolut, which has expanded seamlessly across European borders, a smart, strategic approach can enable rapid scaling within the EU.
The story of Revolut, compared to U.S. challenger banks like Chime, shows that with a savvy navigation of the regulatory landscape and a deep understanding of local market dynamics, it’s not only possible but advantageous to scale regulated tech solutions across Europe.
By investing in a region-by-region approach while building a robust, unified core product, Revolut has proven that European fragmentation can be turned into an asset rather than a hurdle.
Generationally great founders recognize that these challenges, while real, are not insurmountable. They see Europe’s complex market as a proving ground for scalability, resilience, and adaptability—qualities that can ultimately give their companies a competitive edge on the global stage.
Opportunities for Founders and Governments
While Europe faces structural and logistical challenges in AI, there are also unique opportunities. AI adoption, particularly in traditional industries, may proceed faster than previous technological shifts due to the intuitive, agent-based nature of these tools.
As Khachab argues, AI "is the perfect technology for traditional industries" because it allows users to bypass complex interfaces, interacting naturally with machines. This simplicity can enable Europe’s vast industrial sectors to leverage AI with minimal learning curves, offering a significant edge over earlier digital transformations that required more intensive training.
By creating an environment where founders can thrive and fostering innovation in traditional industries, Europe can become a formidable force in the next generation of AI-driven technology.
In Khachab’s words, "we only need one" successful model to prove that European founders can stand toe-to-toe with their global counterparts. With targeted policy support, a proactive approach to industry needs, and a focus on nurturing talent, Europe can get a firm foothold in the future in AI.
