Building a Venture Scale Enterprise AI Company from Spain: David Villalon, CEO of Maisa (Part 7)

Sramana Mitra: Tell me about the sentiment in European enterprises right now regarding AI adoption. You’re succeeding in driving adoption inside European enterprises, which is great. What’s going on?

David Villalon: I think the market has been both overpromised and overhyped. You see two types of companies: those that have tried and failed—which is about 95%, according to an MIT report last week—and those still trying to figure it out.

Many have invested in AI projects that didn’t deliver, and now there’s internal pressure to get real results. They’re willing to buy solutions that actually work out of the box, and that’s where we come in.

However, users are also becoming burned out by all the noise and confusion. Everyone on LinkedIn is claiming success and transformation, but in reality, that’s rarely true. This creates pressure to invest in AI, leading to expensive mistakes—buying tools they don’t understand or following consultants who don’t fully grasp the technology.

We take a contrarian approach. We understand their frustration and focus on helping them succeed quickly. That’s why we don’t prioritize making money from services—we just want to prove our value fast. Once they see results, they regain confidence after all the noise and disappointment in the market. That’s the overall sentiment I see: high frustration but also readiness for real, proven results.

Sramana Mitra: What I find interesting about your company—and what I think makes you successful—is that you have specific use cases you can deliver in production, with reference customers.

In our One Million by One Million (1Mby1M) B2B sales strategy curriculum, we call this the “pain extraction question.” You identify a real pain point, understand it deeply, and solve it with a production use case. That’s an excellent B2B sales strategy. Don’t you agree?

David Villalon: I completely agree. In fact, I was discussing this earlier today. We’ve identified three or four strong use cases, which is great.

But it also ties into pricing. If a customer only uses one small use case, we might seem expensive. However, when they scale to multiple use cases, they see the real value and consider us very affordable. That’s why our pricing strategy has to reflect customer maturity—encouraging upselling and helping users discover new use cases.

We’re still learning, just like the rest of the market. Even OpenAI keeps adjusting its pricing model—from unlimited to credits to new approaches—because this space is evolving so fast.

Sramana Mitra: I agree. In B2B AI use cases, your strategy makes a lot of sense. Subscription pricing is the right way to go. Leading with one or two strong use cases, then expanding to five or ten more, is a smart growth model. Helping users learn, identify new opportunities, and automate internally is an excellent approach. You’re on track to build a great company.

David Villalon: Hopefully. We’ll do our best to make that happen.

Sramana Mitra: Good luck. Very nice to meet you. I’ll follow your work and keep in touch.

David Villalon: Thank you. Great questions, and great meeting you. Bye.

This segment is part 7 in the series : Building a Venture Scale Enterprise AI Company from Spain: David Villalon, CEO of Maisa
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