5 Essential GTM Lessons from Building an AI Company Before the AI Boom
In 2016, when most financial institutions were still asking “what is AI?”, Axion AI was already building deep learning solutions for financial markets. In a recent Category Visionaries episode, founder Daniele Grassi shared how they turned early-market skepticism into a competitive advantage. Here are the key GTM lessons from their journey:
- Play the Long Game in Conservative Markets
When entering conservative markets like financial services, quick wins often come at the cost of long-term credibility. “A very successful ex startup founder who became millionaire told me, yeah, you are getting into a ten year business. This will not be a short ride,” Daniele recalls. Instead of chasing rapid growth, Axion focused on building lasting trust.
Their approach was grounded in technical excellence: “You cannot really sell smoke, okay? Because yeah, if you sell small and you ride the hype, then you may have short term success, but then if your reputation gets a hit, you’re done.” This was particularly crucial because, as Daniele notes, “In the financial sector, the stakes are high. And in large institutions, sometimes it’s better for the people working in it not to make mistakes rather than go beyond expectations.”
- Use Strategic Partnerships as Trust Multipliers
Rather than trying to build credibility from scratch, Axion leveraged established institutions’ reputations. They joined ING’s acceleration program in Amsterdam, which led to investment and crucial introductions. UniCredit followed as their second major investor, further validating their approach.
But their masterstroke was bringing on industry heavyweights as advisors. “I think it is very important for a startup to get sort of sponsorship from relevant person in the industry they’re selling to,” Daniele explains. These relationships provided the pedigree needed to open doors in conservative institutions.
- Choose Your Location and Structure Strategically
The mechanics of building a deep tech company in Europe required careful planning. “It is true that it’s easier to get fundraising, to get funds and investments in certain parts of the world rather than in others. It’s true that being Europe is way more difficult than being in the US. It’s true that being in Italy is particularly difficult,” Daniele shares. The solution? “Be very mindful in how you set up your company, where do you incorporate it, etcetera. That is important because that really makes a difference in how easy you will get money afterwards.”
- Maintain Focus in the Face of Competition
Instead of trying to serve every market segment, Axion maintained laser focus on investment management, specifically in adding alpha to investment strategies. This specialization helped them build expertise that generalist AI companies couldn’t match. When competitors emerged, their depth of experience set them apart: “When we find competitors or other companies like pitching, maybe the same prospect, they often are not as focused as us, not as technology and value focused as us, and not scientifically sound and with a long track record as us.”
- Prepare for Market Evolution
The challenges of selling AI have evolved dramatically. Initially, Axion had to explain basic concepts: “The first question we always got was very simple, what is AI?” Today, the challenge isn’t skepticism but differentiation in a crowded market. “The biggest problem from us in terms of competition are not other companies that say, are serious players in Syria, but more the, let’s say the smoke again, AI smoke that is out there because now every company says they are doing some kind of AI.”
Looking ahead, Daniele predicts AI will become table stakes: “In five years, AI would be an essential and core component of any investment strategy… It would not just be a matter of like having AI to get energy, would be a matter of having AI to stay in the game.”
For founders building deep tech startups today, these lessons remain relevant even as the market matures. While explaining AI may no longer be necessary, building trust through strategic partnerships, maintaining focused expertise, and thinking long-term are still crucial for success in conservative markets. The key is to build fundamental advantages that persist even after the technology becomes mainstream.