AI startups in Luxembourg: data vs founder reality

Startup Luxembourg has published its latest study on AI startups and scaleups in Luxembourg, highlighting key facts, figures and insights. The data shows how the country has developed a dynamic ecosystem of companies leveraging artificial intelligence across different sectors.

However, numbers only tell part of the story. To complement the data, we asked founders from the Luxembourg ecosystem and our own experts to react to common assumptions about AI startups. How do their experiences compare with the statistics? Explore the answers below and dive deeper into the Luxembourg AI startups ecosystem report including the latest figures. 

1. Is it true that AI startups have an easier time raising funding?

What founders say: 

“Honestly, I would turn this around. AI is not a fundraising shortcut; it is becoming table stakes. Investors do not write cheques just because you have AI in your deck. They want to see traction, real outcomes and proof that it actually works. If anything, the risk is now the opposite: if you are not AI-native or not really using AI in what you build, that is the harder conversation. The bar has moved, just not in the way most people expect.”

Panos Meintanis, CEO & Co-Founder, Deelan AI

“It is easier to get attention, not funding. 'AI' gets you into the room faster because everyone wants to look like they are not missing the wave. (Many investors, honestly, do not even understand what this is all about...)  But once you are at the table you still need traction, real revenue, and a defensible model. Investors are more sceptical now because they have seen too many 'AI' decks that were just a ChatGPT wrapper. The label opens doors.”

Casius Morea, CEO, EmailTree.ai

What the research says:

AI attracts ~53% of global venture capital deal value, but funding is concentrated in megadeals and top AI players heavily concentrated in the United States. (Source: “Artificial intelligence (AI) megadeals fuel venture capital rebound, but hide deepening geographic and sectoral divides”, World Intellectual Property Organisation (WIPO))

2. Is it true that having an AI label guarantees investor interest?

What founders say:

“It might guarantee a first meeting, not a signed term sheet. The AI tag gets you attention, but investors quickly dig past the buzzword to check if there's real substance behind it.”

Reyhaneh Niknejad Co-founder & Head of Business Development, Elora

“AI is booming right now and the label will almost certainly get you meetings. But getting interest isn't the same as getting funded. Investors will still ask: Does it solve a real pain for customers? Is your addressable market large enough? Are your metrics promising? Do they believe in your founders? An AI label opens doors, but you need all the other pieces, product-market fit, team credibility, scale potential, to actually close funding.”

Jonas Mareels, Senoir Founder's Associate, ClimateCamp

What the research says:

Venture capital investors are extremely selective and invested capital is concentrated in fewer companies despite AI hype. (Source: “Artificial intelligence (AI) megadeals fuel venture capital rebound, but hide deepening geographic and sectoral divides”, World Intellectual Property Organisation (WIPO))

3. Is it true that AI products are easier to build today?

What founders say:

“Prototypes are faster to build. However, it is important not to over-engineer solutions or create fast and ‘cool’ features that customers never asked for.” 

Dr. Jeff Mangers, CEO & Co-founder, Crab Traceability Systems

“Building a flashy demo? Absolutely! It is absurdly easier than three years ago. Building something reliable, secure, and trusted enough for an enterprise or a government client to actually run their operations on, that is another story. The gap between 'AI demo' and 'AI in production, GDPR-compliant and auditable is still enormous. That is where most of the real work, and failures, happen.”

Casius Morea, CEO, EmailTree.ai

What the research says:

Building AI products is certainly easier today. Advances in generative AI and tooling have lowered barriers and accelerated prototyping, with over 80% of developers reporting productivity gains from AI tools. Rapid growth in AI startup creation supports this. (Source: “State of AI-assisted Software Development 2025”, Google Cloud DORA research program)

4. Is it true that scaling AI startups is easier than traditional startups?

What founders say:

“There is real upside, you can test faster, pivot your product or go-to-market approach without losing months and run experiments you could not before. That reduces risk early on. But everyone has access to the same tools. The advantage is not the technology, it is how well you execute. Learning fast matters, but so does knowing what to do with those insights. In the end, scaling is still a people and process challenge.”

Panos Meintanis, CEO & Co-Founder, Deelan AI

“AI can help you scale certain operations faster, especially anything involving automation. But scaling a company, hiring, sales, customer trust remains just as hard as for any other startup.”

Reyhaneh Niknejad Co-founder & Head of Business Development, Elora

What the research says:

Scaling AI startups is not necessarily easier than scaling traditional startups. While many startups adopt AI, only a small share successfully translate it into scalable business value, highlighting persistent challenges in moving from experimentation to impact. (Source: “AI adoption, adaptation and creation by European startups”, Google for Startups & Notion Capital)

Learn more about AI startups in Luxembourg in the full ecosystem report.