Payroll Accounting without Experts? How AI Helps in 2026

According to a recent study by the Federal Association of Personnel Managers, medium-sized companies receive an average of over 300 applications per year for positions in payroll accounting, with less than 10% meeting the required qualifications. This sobering reality is also reflected in the DIHK Skilled Workers Report 2023: 42% of companies cannot fill open positions in accounting for the long term.

The consequences are dramatic: Overworked teams, rising error rates, and delayed payroll processing. Small and medium-sized enterprises are particularly hard hit – they compete with large corporations for the few available skilled workers. Meanwhile, the demands on payroll accounting are steadily increasing: New collective agreements, more complex working time models, and constantly changing legal requirements increase the workload.

However, while HR departments desperately search for qualified staff, an alternative solution is emerging: Artificial intelligence is already taking over up to 70% of manual routine tasks in payroll accounting today. Modern AI systems validate data, check plausibility, and create standardized evaluations – and do this around the clock without signs of fatigue or careless mistakes. The crucial question is: How can companies use this technology to compensate for the shortage of skilled workers?

Current Situation: Skilled Worker Shortage in Payroll Accounting

The numbers speak a clear language: In the first quarter of 2023, positions in payroll accounting remained unfilled for an average of 187 days – a historic high. The Federal Employment Agency currently records 4,300 open positions in the field of payroll accounting, while only 2,100 job-seeking skilled workers are available.

The financial damage to companies is significant. An analysis by DATEV shows: Errors in payroll accounting cost German companies an average of 27,000 euros annually – trending upwards. Particularly critical: Due to the overload of existing employees, the error rate increases by up to 40%.

The effects extend far beyond simple payroll accounting. HR departments are postponing strategic projects, digitalization efforts are stalled, and employee satisfaction is measurably declining. A survey by the Federal Association of Personnel Managers (BPM) shows: 67% of HR departments feel significantly restricted in their ability to act due to the shortage of skilled workers.

What AI Can Already Do in Payroll Accounting

The reality of AI-supported payroll accounting exceeds many expectations today. Modern systems like project b. not only automate individual steps but also take over entire process chains. One example: The automatic processing of sick notifications – from digital capture to calculating wage continuation to generating reports to health insurance. What used to require 30 minutes of manual work is now done by AI in seconds.

A detailed overview of the current AI processes in payroll accounting shows impressive efficiency gains. This is particularly evident in the error rate: While humans make an average of 3-4% errors in manual data entry, the AI error rate is below 0.1%. At the same time, the system continuously learns – the longer it is in use, the more precise the results become.

Particularly noteworthy is the ability of modern AI systems to learn from exceptional cases. An example from practice: In a medium-sized company with 500 employees, the time required for monthly payroll processing was reduced from four days to six hours today. The responsible payroll clerk now focuses on advising executives and optimizing compensation models – tasks requiring real expertise and providing direct value to the company.

How to Implement AI in Your Payroll Accounting

The transition to AI-supported payroll accounting does not begin with technology, but with a careful analysis of your existing processes. First, track the actual time spent on recurring tasks for two weeks. Experience shows: Usually, 60-70% of the time is spent on routine tasks that can be easily automated. Learn how to use AI in payroll accounting to optimize these processes.

Implementation then occurs in three clearly defined phases:

1. Data Preparation: Standardization of input formats, cleaning historical data

2. Parallel Operation: AI system runs one month parallel to manual accounting

3. Gradual Takeover: Starting with non-critical processes like certification creation

Crucial for success is the early involvement of all stakeholders. Train your employees not only in using the new tools but also explain the advantages: More time for complex cases, less routine work, and lower error rates. A medium-sized company from Stuttgart reports: After initial skepticism, no one wanted to go back to the old system after just two months. The reason: Employees could finally focus on what really matters.

Plan realistically for a full transition of six to eight months. Important: Keep an eye on the DATEV interfaces and clarify early with your tax advisor how the new working method affects their processes. Practice shows: Modern AI systems like project b. integrate seamlessly into the existing software landscape and meet all legal requirements for data protection and documentation.

Finding the Right AI Solution

The choice of the right AI solution is crucial for the success or failure of digitalization. The rule here is: It’s not the system with the most features that wins, but the one that best fits your specific requirements. A recent study by the Digital Association Bitkom shows: 64% of failed AI projects in payroll accounting fail due to a lack of compatibility with existing systems – not because of the technology itself.

Key selection criteria include:

• DATEV interface with certification

• German support with expertise in payroll tax law

• Documented data protection compliance (GDPR)

• References from comparable companies

• Scalable pricing models

How systematically you select AI software for payroll accounting also depends on your company size. While small companies with up to 50 employees are often well served with standardized cloud solutions, medium and large companies usually require individual adjustments. One example: A machine manufacturer with 250 employees specifically looked for a solution that can automatically calculate complex shift allowances. With project b., the company found a platform that met this requirement and also enabled integration with the existing time tracking system.

Be particularly aware of hidden costs: In addition to the obvious licensing fees, costs for training, data migration, and system adjustments often arise. A transparent total cost calculation over 24 months should be part of every selection decision. The good news: Most companies achieve amortization after 8-12 months through saved personnel costs and avoided errors.

Future Outlook 2026/2027: Payroll Trends and Labor Market Forecasts

The development of payroll accounting until 2026 will be shaped by three key trends:

1. Fully automated standard processes

• 90% of all routine payrolls are processed without manual intervention

• AI-supported predictive models identify anomalies proactively

• Real-time payrolls become the standard

2. New competency profiles in payroll accounting

• Shift from data entry to process management and analysis

• Increasing demand for "Payroll Technology Consultants"

• Hybrid profiles: Fach expertise + digital competencies

3. Technological Integration

• Seamless connection of time tracking, personnel management, and payroll accounting

• Blockchain-based salary payments become prevalent

• AI-supported compliance checks in real-time

The Federal Employment Agency predicts a transformation of the job profile by 2026: Instead of traditional payroll clerks, "Digital Payroll Managers" will increasingly be sought. They combine expertise with technological understanding and project management skills.

Experts expect a rapid consolidation of the market: Small payroll offices without digital expertise will be taken over by larger providers. At the same time, new business models such as "Payroll-as-a-Service" and AI-supported consulting offerings are emerging.

For companies, this means:

• Investments in employee qualification will become more important

• Hybrid work models will prevail

• Stronger focus on strategic HR work

DATEV predicts that by 2026, over 75% of all German companies will use AI-supported payroll accounting systems. The return on investment will decrease to an average of 6 months.

Conclusion

The automation of payroll accounting is no longer an option, but a necessity. The shortage of skilled workers will continue to worsen. Companies that invest in digital processes now gain a crucial competitive advantage. It is important to note: Technology does not replace humans, but supports them. Payroll experts can focus on strategic tasks while software robots take over routine work. The entry does not have to be complex – with the right tools and a step-by-step approach, transformation can be successfully mastered.

Sources

• https://www.dihk.de/de/themen-und-positionen/fachkraefte/beschaeftigung/fachkraefteengpassanalyse-2023

• https://www.datev.de/web/de/aktuelles/datev-news/digitalisierung-der-lohnabrechnung-2023/

• https://www.bitkom.org/Presse/Presseinformation/Ki-Einsatz-Unternehmen-2023

• https://statistik.arbeitsagentur.de/DE/Statischer-Content/Statistiken/Fachstatistiken/Arbeitsmarkt-Arbeitgeber/Arbeitsmarkt-Engpassanalyse-2023

• https://www.bpm.de/sites/default/files/hr-trends-2023-studie.pdf

• https://www.arbeitsagentur.de/datei/arbeitsmarktprognose-2026_ba147950.pdf

• https://www.datev.de/web/de/m/ueber-datev/das-unternehmen/datev-trends-2026/