Europe’s Sovereign AI Drive Needs Both Funding and Buyers

Although record sums of money are flowing into Europe’s artificial intelligence startups, financial backing alone will not secure the region’s control over its technological future. During conversations at the HumanX conference in Amsterdam, a critical missing element became clear: large enterprises and governments must actively purchase the products these startups are developing.

Data from a joint report by Crunchbase and HumanX reveals that European AI startups secured $23 billion in the first half of 2026. This marks a 130% year-over-year increase and represents 55% of the entire region’s venture capital funding. Such an investment boom fuels a central question in the sovereign AI debate: Where should nations direct their resources to retain data control and capture the economic value of the technology?

However, achieving sovereignty does not necessitate controlling every single tier of the AI architecture, according to two industry leaders interviewed live at the event: Fabrizio Del Maffeo, founder and CEO of Axelera AI, and Mehdi Ghissassi, chief product and technology officer at AI71.

Representing perspectives from Europe and the United Arab Emirates respectively, their insights highlighted specific opportunities in specialized hardware and applications. They also emphasized how government directives, purchasing choices, and computing availability ultimately dictate whether AI ambitions translate into genuine economic growth.

Five-layered cake

Nvidia President and CEO Jensen Huang has previously outlined a “five-layer cake” framework for delivering artificial intelligence, which consists of energy, chips, infrastructure, models, and applications.

For Del Maffeo—whose enterprise focuses on inference chips—the primary opportunity lies within the semiconductor tier, especially as AI workloads shift away from centralized data centers and toward edge devices.

“Artificial intelligence will expand from cloud computing, from centralized data centers, to devices closer to us in the physical world,” Del Maffeo stated. “To enable this, you need specific chips which can run efficiently, at a lower cost, to connect these networks that today are running in the cloud. We are here to solve this problem.”

Operating for five years, Axelera AI currently supplies two generations of chips to approximately 600 clients and plans to scale its offerings toward decentralized cloud computing infrastructure.

AI transformation

Based in Abu Dhabi, AI71 collaborates with government bodies and major organizations to facilitate their transition toward AI integration.

Ghissassi noted that the UAE boasts the highest compute per capita globally, alongside abundant, low-cost energy and a strict three-month government mandate requiring every state agency to implement agentic workflows for citizens. The nation’s objective is for AI agents to handle half of all citizen-government interactions over the next two years, he added.

Ghissassi argued that competing directly at the model layer is impractical due to the massive capital requirements and the speed at which models commoditize, leaving room for only two, three, or four viable players.

Instead, the application layer is paramount for maintaining data sovereignty, explained Ghissassi, who previously directed product development at Google DeepMind. “You want to make sure that it stays with you, be it that you’re a government or an enterprise. If you’re giving away your trade secrets and know-how, nobody stops whoever is being a provider to you today, from replacing you.”

In the UAE, success is driven by institutional mandates, fast execution speeds, accessible computing resources via sovereign, on-premises, or global clouds, and strong investment capital dedicated to enterprise transformation, according to Ghissassi.

Conversely, Europe operates as a net importer of energy. While it maintains capabilities in semiconductors, it lacks the full infrastructure for large-scale neural network compute and frontier laboratories.

“We should not be obsessed with controlling the entire stack,” Del Maffeo remarked. Europe must focus on generating domestic value instead of merely paying for external services, he noted. “Creating value means creating a wealthy economy.”

Europe benefits from deep research talent pools and a population of 440 million potential users. However, Del Maffeo pointed out that the corporate culture of large enterprises procuring technology directly from startups is less mature in Europe, depriving the region of the growth flywheel seen in the United States.

“What worries me is that we are a little bit lagging behind, and therefore we are missing this value creation, and this will weaken the economies of Europe,” he concluded.

Related Crunchbase query:

• Europe AI Funding In 2026

Related reading:

• Crunchbase & HumanX 2026 European AI Economy Report: Funding, Innovation and Growth
• Europe Posted Its Strongest Venture Funding Quarter In 4 Years As UK Gains, M&A Holds Up

Illustration: Dom Guzman

Frequently Asked Questions

How much funding did European AI startups raise in early 2026?

European AI startups raised $23 billion in the first half of 2026, marking a 130% increase year over year and making up 55% of the region’s venture funding.

What is Jensen Huang’s “five-layer cake” framework for AI?

Nvidia CEO Jensen Huang defines the five layers of AI delivery as energy, chips, infrastructure, models, and applications.

Why does Mehdi Ghissassi say competing at the model layer is impractical?

Ghissassi notes that the immense capital required and the rapid commoditization of models mean only two, three, or four companies can sustainably afford to compete in that space.

What are Europe’s primary advantages in the AI sector?

Europe boasts deep pools of research talent, a large population of 440 million people, and established strengths within the semiconductor industry.

What challenge hinders Europe’s AI growth compared to the U.S.?

Europe lacks a deeply established corporate culture of large businesses purchasing technology directly from startups, preventing the formation of a strong growth flywheel.