AI in Payroll: Hype or Help?

You are sitting in front of a pile of sick leave notifications. The monthly closing is in three days. The new colleague has already left after six weeks because she felt the work was "too detailed." And then someone comes and tells you that AI will solve all problems.

It's understandable if you wave that off at first.

This article is written for you if you're among the 67 percent of payroll accountants and tax advisors who have heard of AI but don't exactly know what it means for their everyday work. No marketing promises, no buzzwords. Instead: concrete answers to the questions that really concern you.

Why this topic is currently on everyone's mind

The numbers speak a clear language. According to DIHK Skilled Workers Report, 42 percent of companies cannot fill open positions in accounting long-term. A study by SD Worx from 2024 found that two-thirds of the surveyed executives are already considering using AI in payroll.

The reason is obvious. The requirements are becoming more complex: new collective agreements, changed social security contributions, minimum wage increases. At the same time, there are not enough people to handle all of this.

What used to be handled by three employees is now shouldered by one and a half. The error rate is increasing. So are the overtime hours. And the frustration as well.

In this situation, the word "AI" is mentioned more and more frequently. Not as futuristic speculation, but as a possible way out of a very real problem.

What AI can actually take over in payroll

For a moment, forget the images of robots replacing humans. The reality looks different.

AI in payroll means software that recognizes patterns, validates data, and automates routine tasks. A concrete example: A sick leave notification comes in. Until now, you opened the document, entered the data manually into the system, calculated the continued payment of wages, and prepared the notification for the health insurance. Time spent: about 30 minutes.

With an AI-supported system, it works differently. The software recognizes the document, extracts the relevant data, checks it for plausibility, and creates the necessary notifications. Your task: to take a quick look and approve it. Time spent: under five minutes.

It works similarly for:

• Certificates (employment certificates, earnings certificates)

• Master data changes (new address, bank account, tax class)

• Travel expense reports

• Preliminary notifications to social insurance carriers

The error rate decreases measurably. While manual data entry has a 3 to 4 percent error rate, AI-supported systems have an error rate of under 0.1 percent.

What AI cannot do

Here it gets honest. AI has clear limits:

Special cases that require discretionary power cannot be decided by software alone. An employee asks whether their training counts as working time? This requires human judgment. A complicated divorce case with maintenance claims? The same applies.

Communication with employees remains human. If someone has questions about billing, they want to talk to a person, not a chatbot.

And finally: Strategic consulting of management on compensation models, social benefits, or personnel costs. This requires experience, context, and sensitivity.

The formula is simple: AI takes care of the repetitive tasks. You focus on what requires expertise.

"Will my job become obsolete?"

The short answer: No. The longer answer: The job profile is changing.

The facts speak for themselves. In companies that are already using AI, no payroll jobs have been eliminated so far. What has happened is that the work has shifted. Less data entry, more quality assurance. Less routine work, more consulting.

An example from practice: A medium-sized company with 350 employees switched to an AI-supported precursor system. The responsible payroll accountant previously needed four days for the monthly closing. Now it takes six hours. The remaining time is spent on tasks that were left undone before: optimization of the company pension scheme, consulting department heads on bonus models, training for new managers.

Your comment: "I am finally doing what I was actually trained for."

The Federal Employment Agency forecasts a transformation of the job profile by 2026. There will be an increasing demand for "Digital Payroll Managers" who combine expertise with technological understanding. Salaries in this field are rising.

DATEV and AI: Not either-or

A question that comes up regularly: "What is better than DATEV?" 

The question is wrongly formulated. Modern AI solutions do not replace DATEV. They work in front of it.

The concept is called "precursor system." It works like this: All data from the company, from various sources and formats, first flows into the AI system. There, they are checked, structured, and prepared. Only then do they go on to DATEV, in the correct format, complete and validated.

For tax advisors, this means: The client data no longer comes as Excel chaos or through email ping-pong. It comes well-prepared, with documented changes and clear origins.

The DATEV itself is working on similar approaches. The integration of AI precursor systems into existing DATEV workflows is now technically solved and certified.

Who is behind project b.

Before you engage with a new provider, you want to know who is behind it. A legitimate question.

project b. was founded in 2023 in Munich. The two founders bring completely different, but perfectly complementary experiences:

Stephan Weber is a real expert in payroll accounting. As Head of Product at PayFit, he helped build the German product for payroll. His stages at PayFit France and Monite have shown him how complex the German payroll landscape really is. It is no coincidence that Germany ranks second among countries with the highest complexity in payroll. Weber knows the pain points firsthand.

Aaron Hayos brings the Silicon Valley perspective. As VP Finance at Homebound, a fast-growing US startup, he has experienced what happens when financial processes do not keep pace with company growth. His experience from the American startup and scale-up world: Processes must be designed to be scalable from the outset.

The combination works: Weber understands the intricacies of German payroll accounting in detail. Hayos knows how to build technology that grows with companies. Together, they have developed software for two years, directly embedded in payroll offices and tax consulting firms. Not in the back office, but in everyday work.

In October 2023, project b. completed a seed financing round. The investors:

• Lakestar (known for investments in Spotify, Delivery Hero)

• QED Investors (Klarna, Credit Karma)

• Foundamental

• First Momentum Ventures

These investors evaluate hundreds of startups per year. That they have chosen a payroll tool shows that the problem is significant enough, and the solution promising.

Three ways to approach the topic

You don’t have to decide anything today. But if you want to find out whether AI in payroll is relevant for you, there are straightforward options:

• Webinars: project b. regularly offers free online sessions. No sales events, but insights into concrete use cases. What works? What doesn’t? What mistakes do others make? An hour that provides orientation.

• Personal conversation: If you prefer to talk specifically about your situation, you can book a non-binding consultation. 30 minutes during which you can ask questions and assess whether this topic is a priority for you.

• Demo access: For all those who like it practical. Test the platform with real data and see for yourself what automation in everyday life would look like.

All three options are free of charge. No subscription, no hidden catches.

Conclusion: Understanding comes before deciding

AI in payroll is not a hype that will disappear. The technology is here, it works, and it is being used by more and more companies.

This does not mean that you must change everything tomorrow. But it does mean that it is worth understanding the topic. Knowing what is possible. And then deciding whether and when it becomes relevant for you.

project b. offers an entry point that costs nothing but a little time. The rest is up to you.

Sources

• DIHK Skilled Workers Report 2023

• SD Worx Study on Payroll 2024

• Federal Employment Agency: Labor Market Forecast 2026

• deutsche-startups.de: Project B Funding (October 2023)