Dutch payments giant Adyen, for years regarded as a model of efficiency in the fintech sector, has reached a turning point that perfectly illustrates the current dilemmas of Silicon Valley and European tech hubs. Although the company closed the second half of 2025 with a solid 21 per cent increase in net revenue, financial markets reacted violently. The 15 per cent drop in shares is a signal that investors have stopped feeding on promises of scale alone and have begun to rigorously hold companies accountable for volume dynamics.
A key challenge for Adyen remains that the €745 billion worth of transactions processed missed analysts’ ambitious forecasts. In a world of high-margin payments, where every basis point matters, the underestimation of demand by nearly €26 billion raises concerns about market saturation. Nevertheless, the company’s business model is showing great resilience. Higher transaction fees managed to partially cushion the lower traffic, allowing the EBITDA margin to remain at 53%.
Adyen’s strategy is evolving towards so-called ‘unified commerce’ (Unified Commerce). While traditional e-commerce is facing strong competition, Adyen is aggressively entering stationary shops. The expansion of the partnership with Starbucks into European markets and the operation of terminals for Uber have translated into a 26 per cent jump in physical transactions. This is where the greatest potential for optimisation lies: Adyen does not want to be just a ‘pipe’ for transferring money, but an intelligent analytics layer.
CFO, Ethan Tankowsky, points to a new foundation for growth: agent-based artificial intelligence. Unlike many companies that treat AI as a marketing add-on, Adyen has the raw material of the highest order – clean, structured, real-time transactional data. The planned hiring of 600 specialists while automating internal processes is expected to push margins to 55% over the next two years.
Adyen shows that the future of payments lies not in scale per se, but in the ability to turn raw purchase data into predictive tools that help retailers understand the customer better than they do. The question is whether the capital market will be patient enough to wait for the results of this transformation.
