Betting on the fifth horse

Oscar Werner at Gilion explains how AI should change the way we value companies

 

The rise of agentic architectures has fundamentally changed company evaluation. Employees we call super individual contributors, or Super-ICs, can now achieve output that previously required entire teams, thanks to AI tools. Multi-agent workflows and orchestration support have become an operational reality and are frequently becoming a necessity for businesses to stay competitive.

 

However, the traditional ways to determine a company’s performance have not kept pace with technological evolution. When five people with AI tools can match the output of what fifty people could achieve just a few years ago, the need to use deep data to separate true performance from “pretty slides” at a very early stage has increased dramatically. Yet the majority of financial institutions still base funding decisions on historical Profit and Loss (P&L) statements, a presentation, and some interviews.

 

The new trove of available data from agentic AI has made it easier to both identify and evaluate the fourth, fifth, and sixth horses in the race. These companies don’t necessarily fit the traditional VC model; they may not easily stand out as the most glittering unicorns, but are growing 20-50% annually with strong unit economics. Over time, massive value is created in this category of steady-growth businesses. 

 

These slower and steadier businesses with resilient foundations in their DNA also make up a major portion of the total growth in the tech sector. Other companies may grow at faster rates, typically 50% to 200%, and can easily attract VC money as a result, but they are often in a strong position to avoid unnecessary dilution and keep in control.

 

Europe faces a €375 billion funding gap for growth-stage companies, because quality businesses growing steadily but not explosively fall through the cracks. Many banks won’t lend without multiple years of backwards-looking accounting data. Yet these companies are already proven, if you just look at the underlying data and trends.

 

Many VCs are chasing potential 100x returns – one huge winner to offset their slew of losses - while others are investing the vast majority of time and capital in the latest, hottest trends. As a result, solid companies in less ‘shiny’ segments, or without the newest jargon description, don’t get funded.

 

Meanwhile, even a junior developer who is proficient with AI tools can generate impressive early metrics such as growing customer numbers, high net retention rate and decreasing customer acquisition costs - the traditional signals investors rely on. Some, who manage to ride the hype curve, will be rewarded with huge funding rounds and sky-high valuations. However, many of these same companies will struggle to demonstrate sustainable value creation in the long run. 

 

As the new agentic era is ushered in, the best businesses frequently share common evolved traits: strong, predictable revenue growth, deep moats that AI can’t easily replicate, and genuine customer value creation that survives when competitors can build similar features in days instead of years. These businesses might not always generate headlines, but they generate returns.

 

Understanding which companies have resilient foundations early requires deeper analysis that looks meticulously into a company’s data, not only historical P&Ls. During the 2022-2023 tech downturn, companies with strong customer retention and working unit economics continued growing while others failed.

 

This isn’t about taking more risk – it’s about understanding risk better. It’s about being radically transparent between the investor and the company. A company that shares all its performance metrics will be better understood, and in return will get better funding. AI-informed financial decisions founded on vast data sets are inevitable because they will be more accurate. The question becomes: Who will build the infrastructure to make them possible?

 

Rather than trying to develop this infrastructure internally from scratch, some forward-thinking institutions understand this fundamental market shift and are beginning to adapt. Historical banking systems and static, offline metrics cannot keep pace with modern data-driven performance evaluation, which is why platforms like Gilion are harnessing agentic AI to analyse one million times the data points when making investment decisions.

 

Looking at the wider funding ecosystem, this evolutionary leap in financial evaluation technology gives European companies with strong fundamentals inherent advantages. They can now secure more funding from better sources that match their long-term approach, and can grow faster as a result.

 

I look for companies with a plan and a dream, and data that shows that they are on the way there. Many of these founders are increasingly looking for patient non-dilutive capital over aggressive venture terms. They understand that sustainable growth often creates more value than the scale-at-all-costs approach that the VC model has given rise to. While it’s easier to create impressive-looking products, it’s more difficult to build lasting customer value. The companies that understand this distinction will define the next decade.

 

A large share of the market is moving decisively toward profitability over whirlwind growth, accelerated by the ease with which impressive-looking but hollow companies can now be created.

 

As it stands, many established players are encumbered by legacy thinking and protecting existing revenue streams, while new entrants build natively for the agentic AI era. The divide between companies that understand the gigantic AI transformation ahead, and those that don’t, will only continue to widen. Those that do will drive the next frontier of European tech, and will capture competitive advantages.

 

The infrastructure to support this recalibration is already being built. Deep data and AI-driven risk assessment, extreme transparency between investors and founders, long-term financing centred on real value creation, and founders who grasp that fundamentals all matter more than ever - these elements are tessellating to redefine the European tech ecosystem.

 

Europe doesn’t need to copy Silicon Valley’s playbook. We need to create our own winning formula. There are times when aggressive scaling is appropriate. We should also build an entire ecosystem that values performance over profile, sustainable growth over growth-at-all-costs, and measurable value over vanity metrics. Here in Europe, the talent exists. The capital is available. The infrastructure is being built.

 

The fourth, fifth, and sixth horses might not always win the sprint. But in a world where anyone can create a short-term mirage of value with AI, they’re the ones to watch. 

 

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Oscar Werner is CEO of Gilion

 

Main image courtesy of iStockPhoto.com and hyejin kang