This is how you use AI in payroll.

Anyone working in payroll knows the scenario: An email arrives with a sick leave notification. The attachment needs to be opened, the data extracted, the correct employee found in the system, and the absence recorded. Then the next email. And the next one. Timesheets, address changes, new bank details. Every piece of information must be processed manually.

This routine work consumes time. Time that is lacking for the actual core competency: accurate billing and advice. This is where artificial intelligence comes into play. Not as a replacement for professionals, but as a tool that takes away repetitive preliminary work.

At project b., the AI assistant RITA takes on this task. She structures incoming data, assigns it to the correct records, and prepares it for review. The result: 85 percent of the data is automatically structured before a clerk even sees it.

The Most Important Points in Brief

AI automates data capture: Emails, timesheets, and documents are automatically structured and assigned to the right employees.

Humans retain control: RITA makes suggestions, clerks review and approve in the cockpit.

Integration instead of isolated solutions: Ready-made interfaces to DATEV, SBS, and Agenda allow for direct integration into existing payroll systems.

Seamless workflow: From data capture to review to GDPR-compliant payslip distribution, everything runs on one platform.

What AI Means in Payroll

The term artificial intelligence often raises false expectations. Some picture a system that calculates salaries completely autonomously and initiates transfers. Others fear that machines will soon replace payroll clerks.

The reality lies in between. AI in payroll means: intelligent support for structured tasks. The system recognizes patterns in documents, extracts relevant information, and assigns it. The decision-making authority remains with the human.

RITA, the AI assistant from project b., embodies this approach. She reads incoming emails, identifies the content (sick leave, address change, timesheet) and suggests which employee and data field the information should be assigned to. The clerk sees the suggestion, reviews it, and confirms with a click. Or corrects it if necessary.

This principle distinguishes modern AI systems from simple automation. An automated rule can only cover predefined scenarios. AI also recognizes variations and learns from corrections.

Processing Master Data and Transaction Data

Master data forms the foundation of every payroll: name, address, bank details, tax class, social security number. Transaction data captures what changes: working hours, absences, bonuses.

Traditionally, this information arrives at the payroll office through various channels. The managing director sends an email with a new employee attached. The HR department reports a resignation by phone. A foreman submits handwritten timesheets.

Every piece of information must be entered manually. This not only takes time but also poses sources of error. A mistyped IBAN leads to a failed transfer. A forgotten sick leave distorts the billing.

The master data management of project b. digitizes this process. All incoming information flows through a central platform. RITA automatically structures the data.

Example: Sick Leave

1. An email arrives with the subject "Sick Leave Müller"
2. RITA identifies the document type (sick leave certificate)
3. RITA recognizes the employee's name and suggests the appropriate data record
4. RITA extracts the date and the expected duration
5. The clerk sees the suggestion in the cockpit and confirms

The same process works for address changes, new bank details, or working time records. The absence management captures vacation, illness, and special leave. The transaction data processing takes care of variable components such as overtime or bonuses.

Using the Digital Personnel File

Paper files are a thing of the past, at least theoretically. In practice, many companies still have parallel systems: some documents digital, others in folders, some as email attachments on the clerk's server.

This fragmentation complicates work. When searching for an employee's employment contract, one often has to look in several places. This becomes a problem during an audit.

The digital personnel file from project b. creates a central storage location for all employee-related documents. The AI integration goes a step further: When a new document arrives, RITA identifies the document type and automatically assigns it to the correct employee.

A work contract goes into the "Contracts" folder, a salary adjustment goes to "Compensation," a warning goes to "Personnel Actions." The assignment is done automatically, the filing structure remains uniform.

For companies already using a document management system, project b. offers DMS synchronization. Changes are transferred automatically, avoiding duplicate records.

From the Cockpit to Payslip Distribution

The workflow at project b. follows a clear process:

1. Data Entry: Emails, documents, and forms are captured centrally.

2. AI Structuring: RITA analyzes the entries and assigns them.

3. Review in the Cockpit: Clerks see all suggestions at a glance. Each entry shows what needs to be changed and why. With a click, approval or rejection is done.

4. Change Lists: All approved changes are documented. This creates transparency for inquiries and audits.

5. Integration into the Payroll System: Approved data flows directly into the billing system. project b. provides interfaces to DATEV, SBS, and Agenda. Manual transfer is eliminated.

6. Payslip Distribution: After billing, the payslips are automatically distributed to employees. Delivery is done in compliance with GDPR through secure digital channels.

This seamless process eliminates media breaks. Data is entered once and flows through the entire system without re-entry.

Benefits for Payroll Offices, Tax Advisors, and Companies

The benefits of AI in payroll differ depending on the user group.

For Payroll Offices, efficiency is paramount. Those managing hundreds of clients spend a large part of the day on data entry. If RITA takes over 85 percent of this work, more time remains for actual billing and supporting complex cases.

For Tax Advisors, automation alleviates the payroll department's burden. The capacity gained can be used for higher-value consulting services. At the same time, the risk of errors in data entry decreases, easing liability concerns.

For Companies with Their Own HR Departments, AI offers a way to manage growing employee numbers without proportionally increasing personnel costs. Scaling becomes easier because the system grows along.

An often underestimated advantage is consistency. Humans make mistakes, especially in monotonous tasks. An AI works according to the same pattern, whether at eight in the morning or four on a Friday.

Challenges in Implementation

The implementation of AI in payroll is not a given. Three hurdles regularly confront companies:

Data Quality: AI can only work with what it gets. If master data is outdated or inconsistent, even the best AI will produce faulty suggestions. Often, a cleansing of existing data is necessary before implementation.

Employee Acceptance: New systems generate skepticism. Clerks wonder if they will become unnecessary. Transparency helps here: RITA replaces no one; she only takes over the part of the work that no one enjoys doing. The demanding tasks remain with humans.

Integration into Existing Systems: Many payroll offices and tax advisors have been working with DATEV, SBS, or Agenda for years. A new system must not replace this infrastructure but must fit in. project b. addresses this with ready-made interfaces that allow for direct connection.

Those who understand and address these challenges can significantly accelerate implementation. Pilot projects with selected clients or departments help collect experience before broad deployment.

Conclusion: AI as a Partner in Payroll

Artificial intelligence will not revolutionize payroll. But it will change it. The repetitive tasks that currently take hours can be automated. Clerks can focus on what machines cannot do: assessing complex cases, advising clients, taking responsibility.

The approach of project b. shows how this collaboration can work. RITA structures and suggests. The human reviews and decides. The cockpit provides an overview and control. The interfaces ensure smooth integration.

For payroll offices, tax advisors, and HR departments, the question is no longer whether they will use AI. But when and how. The earlier the engagement with the topic begins, the better the competitive position.