AI in Payroll: What is Possible Today and What is Not?

Artificial intelligence is revolutionizing payroll processing. At least that’s what the marketing departments of software providers claim. The reality is more nuanced: while AI delivers real value in certain processes, final human review remains indispensable in many areas. This article separates marketing promises from actual performance and shows where AI stands in payroll today.

The Status Quo: How Far is AI in Payroll?

The numbers are sobering: according to a recent study, 67 percent of German companies do not use AI for payroll processing. Eight percent even believe that AI will not play a role in this area in the future.

At the same time, the Bitkom study 2024 shows that 76 percent of companies use digital payroll systems. The gap between digitalization and AI utilization is therefore considerable.

What Does This Mean for Your Company?

The market is in a transitional phase. Early adopters are gathering experiences, while the majority is still waiting. For payroll offices and tax advisors, there is an opportunity to gain competitive advantages through targeted AI implementation.

What AI Can Actually Do in Payroll

Not all processes in payroll are equally suited for AI support. Here is a realistic assessment:

Master Data Validation: High Maturity Level

AI reliably detects inconsistencies in employee master data:

• Incorrect IBAN numbers

• Implausible address data

• Inconsistencies between tax class and marital status

• Duplicate records

Degree of Automation: 90-95 %

Human Review: Only for detected anomalies

Error Detection in Timekeeping Data: High Maturity Level

AI analyzes patterns in working hours and detects:

• Unusual accumulation of overtime

• Missing break times

• Inconsistencies with duty rosters

• Systematic recording errors

Degree of Automation: 85-94 %

Human Review: Spot checks and edge cases

Document Processing: Medium Maturity Level

AI extracts data from:

• Sick leave notifications (eAU)

• Expense reports

• Income tax declarations

• Certificates

Degree of Automation: 70-80 %

Human Review: For illegible or incomplete documents

Tax Class Changes and Allowances: Medium Maturity Level

AI can provide hints on necessary changes, but:

• Employee decisions require human consultation

• Legal implications must be checked

• Communication with the tax office remains manual

Degree of Automation: 50-60 %

Human Review: Always required

Special Payments and One-time Payments: Low Maturity Level

Boni, severance payments, and special compensations are complex:

• Individual contract clauses

• Tax optimization issues

• Social security law peculiarities

Degree of Automation: 20-30 %

Human Review: Fully required

Comparison Table: AI Maturity Levels by Process

Marketing Promises vs. Reality

The advertising messages from software providers sound enticing. Here is the fact check:

Promise: "Fully Automated Payroll"

Reality: A 100 percent automated payroll does not exist. The more automated a system operates, the less influence human errors have. However, other problems arise: faulty interfaces, software errors ("bugs"), and data inconsistencies. Employees still have control tasks to perform, which are essential.

Promise: "AI Replaces the Payroll Clerk"

Reality: AI changes the role of the payroll clerk, but does not replace it. The tasks shift from operational processing to control, consulting, and exception handling. Complex cases such as audits, special compensations, or international assignments still require human expertise.

Promise: "20% Cost Savings through Automation"

Reality: This figure is realistic but only under certain conditions:

• Consistently digitized workflows

• High share of standardized payroll cases

• Clean master data quality

• Sufficient implementation time

In small companies with few but complex payroll cases, the savings are significantly lower.

Where AI Delivers Real Value Today

Despite all limitations, there are areas where AI already provides significant benefits today:

1. Anomaly Detection Before Payroll Processing

AI systems check input data for plausibility before payroll processing starts. This prevents errors that would otherwise need to be corrected at a high cost later.

Concrete Applications:

• Verification of completeness of timekeeping data

• Matching sick notifications with working hours

• Detection of double bookings

2. Automatic Updates When Laws Change

Modern payroll software automatically updates tax tables, social security contributions, and allowances. This significantly reduces the risk of compliance violations.

3. Self-Service for Employees

AI-powered chatbots answer common questions about payroll:

• "Why was less paid out this month?"

• "What is my vacation entitlement?"

• "When will the Christmas bonus be paid?"

This relieves the HR department from routine inquiries.

4. Predictive Analytics

AI analyzes historical data and predicts:

• Personnel costs for budget planning

• Overtime development

• Turnover risks

Practical Examples: AI in Payroll

Example 1: Automotive Supplier with 200 Employees

A medium-sized automotive supplier in Baden-Württemberg implemented an AI-supported checking system for timekeeping data.

Initial Situation:

• 200 employees in shift work

• Complex surcharge regulations (night, weekend, holiday)

• On average 15 errors per payroll run

Result after 12 months:

• AI automatically detects 94% of errors in timekeeping data

• Error rate in the final payroll decreased by 78%

• Time spent on data verification reduced by 12 hours per month

• ROI achieved after 18 months

Limitation: In special cases such as short-time work or collective agreement changes, manual checking is still required.

Example 2: Tax Consulting Firm with 45 Clients

A tax consulting firm in Munich handles payroll for 45 SMEs.

Initial Situation:

• 45 clients with a total of 800 payrolls/month

• Heterogeneous data sources (Excel, DATEV, paper)

• 2 full-time payroll clerks

AI Implementation:

• Automatic document recognition for sick notifications

• Plausibility check of client data

• Integration with [DATEV via Personio interface](https://www.personio.de/funktionen/datev/)

Result:

• Data entry 60% faster

• Error rate in document processing reduced by 45%

• **But:** Final checking is still done 100% manually

Reason for Manual Check:

• Liability for errors lies with the firm

• Client-specific peculiarities require expertise

• Audits require traceable decisions

The Limits: Where Human Review Remains Indispensable

Legal Responsibility

The liability for erroneous payroll processing lies with the employer or the commissioned tax consultant. AI can provide recommendations, but cannot take on legal responsibility.

Complex Special Cases

Situations that require human judgment:

• Audits and follow-up claims

• Labor court disputes

• Insolvency cases

• Cross-border employment

Consultation and Communication

Employees have a right to understandable explanations regarding their payroll. AI chatbots can answer standard questions, but cannot replace individual consultations.

Data Protection and Compliance

The GDPR places high demands on the processing of payroll data. AI systems must meet these standards, but the responsibility for compliance lies with humans.

What Software Solutions are Available?

The German market offers various AI-supported payroll solutions:

DATEV Payroll

• Traditional market leader in the SME segment with 14 million payslips per month

• Strong integration with tax advisor workflows

• The software is being slowly transitioned to AI capabilities

project b. 

• Award-winning AI platform for payroll clerks and tax advisors (test winner)

• Automatic data extraction from emails and PDFs

• AI-driven error checking before data processing

• Integration into payroll systems, such as DATEV or Agenda

Personio Payroll

• 2024 certified proprietary payroll solution

• AI recognizes patterns in timekeeping and absence data

• Seamless DATEV integration

SAP SuccessFactors

• Enterprise solution for large companies

• AI along the entire employee lifecycle

• AI assistant "SAP Joule" for routine tasks

Deel

• Cloud-native solution for international payroll

• AI for real-time calculations of salaries and taxes

• Focus on compliance in various countries

Conclusion: AI as a Tool, Not a Replacement

AI in payroll is not a panacea, but a valuable tool. The technology has a high maturity level in:

• Data validation and error detection

• Document processing

• Routine inquiries via chatbot

It faces limitations in:

• Complex special cases

• Legal responsibility

• Individual consulting

For payroll offices and tax advisors, AI provides the opportunity to reduce repetitive tasks and focus on value-adding consulting. However, expectations should be realistic: AI supports the payroll clerk but does not replace him or her.

Sources

• [Infoniqa: The Future of Payroll - Automation and AI in Payroll Processing](https://www.infoniqa.com/post/die-zukunft-der-payroll-automatisierung-und-ki-in-der-lohnbuchhaltung)

• [Personnel Management: AI in Payroll]

• [Personio: DATEV Integration]

• [SD Worx: Difference between AI and Automation in Payroll]