What AI startups really need – these tips from top investors
AI is changing everything – including company building. Experienced VCs explain what's important for AI startups now and which criteria determine funding.
Artificial intelligence is currently disrupting proven business models and product strategies around the world – and the technology is changing how companies are created, grown, and financed. Startups in the AI sector see great opportunities in these developments. At the same time, the increasing demands on vision, speed, and differentiation should not be underestimated.
With new advances being made in the AI industry on a weekly basis, some of the traditional benchmarks for companies seem to have become obsolete. What's considered innovative today will be standard tomorrow. Therefore, anyone who wants to impress with their idea must create real added value. The new report "Startup 2025: Building a Business in the Age of AI" reveals what leading venture capitalists are now paying attention to.
In the Snowflake report, eight VCs from Europe and the US – including representatives from Kleiner Perkins, EQT Ventures, Redpoint Ventures, and NewBuild Capital – share insights into their expectations of startups. What unites them is their belief in the transformative potential of AI, but also the realization that not everything with "AI" in its name is automatically future-proof. The differences lie in the technology architecture, product understanding, and go-to-market strategy.
Rohini Chakravarthy of NewBuild Venture Capital sums it up in the report: "With the basic models of generative AI, things can be achieved that were previously not possible, and the interest of the community is great – the brightest minds in the world are working on it." For her, three things count: economic scalability, new business models and a functioning ecosystem.
A central theme of the report is the distinction between "experimental recurring revenue" (ERR) and "annual recurring revenue" (ARR), which corresponds to traditional, ongoing revenue. Especially with young AI products, it's tempting to view initial revenue as a long-term success. However, Sakib Dadi of Stage 2 Capital warns against this: "A trend seems to be emerging for these AI companies: The quality of revenue in terms of customer retention is simply not as high as the quality of revenue from traditional enterprise software."
Patrick Chase of Redpoint Ventures also believes that long-lasting enterprise applications are the goal—short-term hype is of little use. Startups should therefore ask themselves: How can an early experiment turn into a lasting customer relationship?
Many startups present AI as a core feature, but that's often not enough. Sam Teden of Anthos Capital clarifies: "If something was developed solely for AI's sake, leveraging publicly available data without considering how to build a competitive advantage over time, it loses significant appeal to us."
Things get exciting where AI brings tangible efficiency gains. This is the case, for example, in the service industries of law, construction, and healthcare, where digitalization has so far been limited. According to Liam Mulcahy of Kleiner Perkins, these areas are considered underserved markets with enormous potential.
Ultimately, however, many VCs continue to back people and what they represent. Patrick Chase sums it up this way: "The startup phase we invest in is often the pre-production phase. During this phase, we primarily consider the team and the market."
Efficiency is also crucial. Akash Bajwa of Earlybird VC emphasizes that AI is not only transforming the product, but also the company itself: "I would like to see more capital efficiency in companies today, reflected, for example, in not hiring their first marketing employee too early. Many of the marketing, SDR, and BDR activities that would normally be assigned to this person can now be handled with a commercially available AI product."
With one of the largest tech IPOs in recent memory, Snowflake is undoubtedly one of the most successful data startups of the last decade. The company knows only too well how to drive innovation in data-intensive markets. Today, the business supports hundreds of startups worldwide through its "Powered by Snowflake Startup Program."
This report was created precisely from this practical perspective: a guide for founders who want to scale in the era of AI and cloud. Anyone who wants to understand what's important when building a successful AI company will find solid answers in "Startup 2025: Building a Business in the Age of AI."
Know what's important when starting a business in the AI era – click here for the report!
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