AI has forced a complete overhaul of how companies operate day-to-day, reaching into almost every aspect of technical application. This revolution has now gone beyond application and into how businesses are run as a whole. As part of our research for the 2026 Notion Capital Cloud Challengers Report, where we sought to find the top 100 B2B software companies poised to define the next decade, we discovered some interesting developments on the impact of AI.
In the fifth edition of the report, we once again aimed to identify the very best emerging business software start-ups in Europe. As ever, our approach to evaluating and ranking these companies is rooted in data and works from a total universe of early stage companies in Europe. Three pillars form the foundation of our assessment: founders, funding, and product. We firmly believe that for early stage companies these elements provide the most telling signals for future success.
As a result, the insight gained from seeking out the best companies leading the market today, I believe, offers us a picture of where we might expect the market to head in the coming years.
Early-stage founders prioritise experienced hires over junior developers
We interviewed more than 60 founders, and our research shows a strong preference for hiring senior engineers over junior developers as early-stage companies need people who can architect solutions. A striking data point is the volume of new code that is now written by AI: two-thirds of those interviewed said that over 80% is now AI-generated, with many putting the figure as high as 95%. Meanwhile, the concept of the ‘Minimum Viable Team’ is getting leaner. This year’s report shows that the median team size dropped to 10 people, down 29% from last year’s median of 14 and 60% lower than the 2024 cohort’s median of 25.
The productivity gains are real, but they come with a caveat that almost every founder flagged independently: (a) the bottleneck has shifted from writing code to architecting and validating it (e.g. code reviews), (b) instead of hiring multiple junior engineers, teams now hire fewer but more experienced senior engineers who have a broader impact through agents (we’ve heard engineers orchestrating as many as 20 agents at once) and (c) although code velocity increased 5-10x, overall feature velocity has not kept the same pace, largely due to the time required to review code & architecture.
The size of an early-stage company used to be taken as a measure of growth and success; that is no longer the case. Now, senior hires are preferred — often these are senior people with coding skills and good judgement, to ensure quality. We are witnessing a redefinition of what it takes to build a high-potential early-stage company.
The shift to AI-native companies is almost complete
AI-native companies – those whose products fundamentally could not exist without AI — now dominate the Cloud Challengers Top 100 list, with 81% of companies having AI with a core component, up from 50% just one year ago, and 24% a year before that. By next year, I expect it to be taken for granted and the number to be very close to 100%. AI-native companies will ultimately offer products that are cheaper and better, and they will also expand the overall market opportunity. Currently an average company spends around 10% of their operating expenses on software; this new generation of AI companies will also target the other 90% that is not spent on software.
Within the AI-native category, there is a clear split between those that offer vertical, industry-specific, solutions (63%), and those that pursue horizontal, broader, applications (37%). The focus on verticals is significant and shows that founders are opting to apply AI to specific, high-value workflows and building deep expertise that is harder to replicate.
Software has been through many cycles from client-server to cloud to mobile and now AI. AI is the most significant platform shift we have seen for a long time – perhaps ever.
Industrials & Robotics becomes a top category as AI moves into physical-world industries
It would be remiss to assume that the impact of AI is stuck in the digital realm. In this year’s Top 100 list, Developer Tools & Infrastructure remains the largest category with 12 companies, although this sector is not as dominant as it was in 2025. This year, the field is more competitive, with Industrials & Robotics (11 companies) and Sales Enablement & Customer Success (11 companies) sharing the limelight. The emergence of Industrials & Robotics is notable as this segment barely featured in earlier editions of the report.
AI software is now able to learn from and interact with the real world in a way that simply wasn’t possible before. In this way, we are seeing more integrated solutions with software integrated with hardware and, more broadly, with physical environments.This includes next generation manufacturing, robotics, infrastructure monitoring and autonomous vehicles across multiple form factors including cars, trucks, drones and boats.
