In many startups, product, sales and marketing have long been running in high-performance mode. But in the finance department of all places – the area that is actually supposed to secure growth – things are still surprisingly analogous. Copying, matching, manual bookings: As the company scales, central finance processes stand still.
A new survey of specialists from finance, accounting and controlling shows the extent: a quarter of working time goes into manual data entry, another large part goes into invoice processing and recurring analyses. At the same time, only 3% are really using AI comprehensively, while almost a third are not yet using any AI solutions at all. This is a warning signal for fast-growing startups – because without clear structures, the risk of scaling blindly increases.
Where finance is being slowed down today
Despite clear ambitions, the step towards automation is only being achieved slowly. 40% of those surveyed see process automation as the most important driver of transformation, and 38% prioritize corresponding investments – but manual processes continue to dominate in everyday life. For 36%, the effort associated with paper-based processes, scanning or data entry is one of the biggest operational hurdles. This keeps finance teams in operational mode, even as expectations for a more strategic role increase.
This creates a structural risk, especially in startups: fragmented systems, inconsistent data models and a lack of automation slow down finance processes as soon as the company scales. If data is available late or analyzes are created on an uncertain basis, there is no basis for quick and reliable decisions – and growth can come to a halt.
Why AI in finance would actually be perfect
The irony: Hardly any other area is as suitable for AI as finance. Structured, rule-based, data-driven. So actually ideal conditions. AI could automatically classify receipts, detect irregularities, continually update forecasts or support cash flow decisions.
But the bottleneck is rarely in the technology itself. Without a consistent database, integrated systems and clear processes, AI remains piecemeal. What is missing is the infrastructure that makes automation and AI possible.
Finance as a nerve center – not as a brake block
Today, finance sees more of the company than almost any other department: sales, costs, liquidity, investments – everything comes together here. When repetitive tasks are automated, strategic impact immediately increases:
- Decisions are becoming faster
- Risks become visible earlier
- Discussions are more data-based
Many CFOs therefore no longer see themselves as administrators, but rather as designers. But this requires an organization that allows this change.
What female founders should do now
Young companies in particular have a decisive advantage: they can set the course early. Instead of historically grown system landscapes, there is flexibility and this should be used. Specifically, this means:
- Clearly define roles: Who is responsible for which processes?
- Standardize processes, fewer special cases, more standard.
- Building modern tool landscapes: systems that not only collect data, but also make it usable. Rely on automation early, before the complexity becomes too great.
The way out of the AI pilot phase is not a purely technical project, but an organizational one. Companies that understand this transform finance from an operational requirement into a real lever for growth.
The way forward
Finance is at a turning point. Where tables are still maintained manually today, real-time data and automated workflows could set the pace tomorrow. The technology has existed for a long time. The question is whether companies will align their structures in such a way that they benefit from this.
For female founders, the earlier finance is professionally set up, the faster and more resilient a startup can be scaled. AI develops its effect exactly where data is neatly integrated, processes are clearly defined and responsibilities are clearly regulated.
Startups that build this foundation now make better decisions, stay in control of their growth, and avoid losing their success due to Excel limitations.
Methodology of the study
The survey data is based on online interviews with members of the YouGov panel who have agreed to participate in advance. For this survey, a total of 264 people who work in the areas of finance, controlling and financial accounting were interviewed between September 11th and 23rd, 2025.
You can find further information about the study results here.
About the author
Nikolai Skatchkov is co-founder and CEO of Circula, a SaaS fintech from Berlin. He has been working on the digitalization of financial processes for years. With Circula, he has developed a platform that combines expense reporting, digital benefits and company cards. Over 2,800 companies, including DATEV, German Football League, Securitas and AboutYou, already rely on these solutions.
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