D W
EU AI Act: Not High Risk Q1

Sick Leave Processing Agent

Process sick notes in minutes, not days - with full compliance tracking.

Processes sick leave certificates, calculates continued pay periods, manages statutory notifications, and maintains audit trails for health reporting.

Analyse your process
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Assessment

Agent Readiness 84-91%
Governance Complexity 21-28%
Economic Impact 68-75%
Lighthouse Effect 16-23%
Implementation Complexity 21-28%
Transaction Volume Daily

What This Agent Does

Sick leave processing is deceptively simple on the surface and surprisingly complex underneath. A single sick note triggers a cascade of downstream actions: continued pay entitlement calculation, health insurance notification, team scheduling adjustments, and potentially return-to-work coordination - each with jurisdiction-specific deadlines. The Sick Leave Processing Agent receives digital or scanned certificates (including the EU's emerging electronic sick note standards), validates them against employee data and current absence records, calculates continued pay entitlements based on applicable law and collective agreement, and triggers all required notifications within statutory deadlines. It tracks the progression from short-term to long-term absence and flags threshold crossings that change the legal and financial treatment. The agent handles document classification (initial certificate vs. follow-up vs. rehabilitation notification) and routes ambiguous cases - such as overlapping sick periods or pre-existing absence patterns - to HR for review. No medical information is evaluated or stored beyond what is legally required for payroll and statutory reporting.

Micro-Decision Table

Human
Rules Engine
AI Agent
Each row is a decision. Expand to see the decision record and whether it can be challenged.
Receive certificate Classify document type (initial, follow-up, rehabilitation) AI Agent

Document classification from structured and semi-structured inputs

Decision Record

Model version and confidence score
Input data and classification result
Decision rationale (explainability)
Audit trail with full traceability

Challengeable: Yes - fully documented, reviewable by humans, objection via formal process.

Validate certificate data Check completeness, dates, physician credentials Rules Engine

Rule-based validation against statutory requirements

Decision Record

Rule ID and version number
Input data that triggered the rule
Calculation result and applied formula

Challengeable: Yes - rule application verifiable. Objection possible for incorrect data or wrong rule version.

Match to employee record Link certificate to correct employee and absence history Rules Engine

Deterministic matching on employee ID and date ranges

Decision Record

Rule ID and version number
Input data that triggered the rule
Calculation result and applied formula

Challengeable: Yes - rule application verifiable. Objection possible for incorrect data or wrong rule version.

Check for overlapping absences Detect conflicts with existing leave, other sick periods Rules Engine

Date-range overlap detection against absence calendar

Decision Record

Rule ID and version number
Input data that triggered the rule
Calculation result and applied formula

Challengeable: Yes - rule application verifiable. Objection possible for incorrect data or wrong rule version.

Calculate continued pay entitlement Determine weeks of entitlement remaining per statutory rules Rules Engine

Statutory calculation based on employment duration and absence history

Decision Record

Rule ID and version number
Input data that triggered the rule
Calculation result and applied formula

Challengeable: Yes - rule application verifiable. Objection possible for incorrect data or wrong rule version.

Trigger statutory notifications Send required notifications to health insurance within deadline AI Agent

Automated notification with deadline tracking - no discretion needed

Decision Record

Model version and confidence score
Input data and classification result
Decision rationale (explainability)
Audit trail with full traceability

Challengeable: Yes - fully documented, reviewable by humans, objection via formal process.

Flag threshold crossings Alert HR when absence reaches long-term threshold Rules Engine

Rule-based threshold monitoring triggers escalation

Decision Record

Rule ID and version number
Input data that triggered the rule
Calculation result and applied formula

Challengeable: Yes - rule application verifiable. Objection possible for incorrect data or wrong rule version.

Route ambiguous cases Escalate unclear patterns or incomplete documentation to HR AI Agent

Pattern recognition for edge cases requiring human assessment

Decision Record

Model version and confidence score
Input data and classification result
Decision rationale (explainability)
Audit trail with full traceability

Challengeable: Yes - fully documented, reviewable by humans, objection via formal process.

Update time and payroll systems Record absence days and adjust pay calculation accordingly AI Agent

Automated downstream sync after validated processing

Decision Record

Model version and confidence score
Input data and classification result
Decision rationale (explainability)
Audit trail with full traceability

Challengeable: Yes - fully documented, reviewable by humans, objection via formal process.

Decision Record and Right to Challenge

Every decision this agent makes or prepares is documented in a complete decision record. Affected employees can review, understand, and challenge every individual decision.

Which rule in which version was applied?
What data was the decision based on?
Who (human, rules engine, or AI) decided - and why?
How can the affected person file an objection?
How the Decision Layer enforces this architecturally →

Prerequisites

  • Digital sick note intake capability (portal, email, or e-certificate interface)
  • Employee absence history accessible to the agent
  • Statutory continued pay rules codified per jurisdiction
  • Health insurance reporting interface
  • Integration with time management and payroll systems
  • Data processing agreement covering health-related data (GDPR Art. 9 special category)

Governance Notes

EU AI Act: Not High Risk
Not classified as high-risk under the EU AI Act - the agent processes documents and applies deterministic rules without making decisions about the employment relationship. However, GDPR Article 9 applies because sick leave data constitutes health-related special category data. Processing must be based on employment law obligations (Art. 9(2)(b)) and requires enhanced security measures. The agent must not perform pattern analysis that could constitute health profiling. A Data Protection Impact Assessment is mandatory.

Infrastructure Contribution

The Sick Leave Processing Agent establishes document classification, deadline tracking, and statutory notification patterns that are reused by the Leave of Absence Agent, Compliance Training Agent, and any agent dealing with time-sensitive regulatory notifications. The health data handling protocols built here set the standard for all future agents processing special category data. Builds Decision Logging and Audit Trail used by the Decision Layer for traceability and challengeability of every decision.

Does this agent fit your process?

We analyse your specific HR process and show how this agent fits into your system landscape. 30 minutes, no preparation needed.

Analyse your process

What this assessment contains: 9 slides for your leadership team

Personalised with your numbers. Generated in 2 minutes directly in your browser. No upload, no login.

  1. 1

    Title slide - Process name, decision points, automation potential

  2. 2

    Executive summary - FTE freed, cost per transaction before/after, break-even date, cost of waiting

  3. 3

    Current state - Transaction volume, error costs, growth scenario with FTE comparison

  4. 4

    Solution architecture - Human - rules engine - AI agent with specific decision points

  5. 5

    Governance - EU AI Act, works council, audit trail - with traffic light status

  6. 6

    Risk analysis - 5 risks with likelihood, impact and mitigation

  7. 7

    Roadmap - 3-phase plan with concrete calendar dates and Go/No-Go

  8. 8

    Business case - 3-scenario comparison (do nothing/hire/automate) plus 3×3 sensitivity matrix

  9. 9

    Discussion proposal - Concrete next steps with timeline and responsibilities

Includes: 3-scenario comparison

Do nothing vs. new hire vs. automation - with your salary level, your error rate and your growth plan. The one slide your CFO wants to see first.

Show calculation methodology

Hourly rate: Annual salary (your input) × 1.3 employer burden ÷ 1,720 annual work hours

Savings: Transactions × 12 × automation rate × minutes/transaction × hourly rate × economic factor

Quality ROI: Error reduction × transactions × 12 × EUR 260/error (APQC Open Standards Benchmarking)

FTE: Saved hours ÷ 1,720 annual work hours

Break-Even: Benchmark investment ÷ monthly combined savings (efficiency + quality)

New hire: Annual salary × 1.3 + EUR 12,000 recruiting per FTE

All data stays in your browser. Nothing is transmitted to any server.

Sick Leave Processing Agent

Initial assessment for your leadership team

A thorough initial assessment in 2 minutes - with your numbers, your risk profile and industry benchmarks. No vendor logo, no sales pitch.

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All data stays in your browser. Nothing is transmitted.

Related Pages

Decision Layer
Governance layer between AI agent and target system. Every decision documented and challengeable.
Co-Determination & AI
Works council, works agreements, and co-determination as architecture constraint.
HR AI Agents
All HR agent services at a glance.
HR Agent Readiness
7 questions, 3 minutes. How ready is your organisation?
Assessment eBook
15 questions for your leadership team as PDF.

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Frequently Asked Questions

Does the agent access or analyse medical diagnosis information?

No. The agent processes only the data elements legally required for payroll and statutory reporting: dates, duration, and certificate validity. Diagnosis codes are not extracted, stored, or analysed.

How does the agent handle electronic sick notes?

The agent supports both traditional document intake and emerging electronic sick note standards (such as the German eAU). The processing logic is the same - only the intake channel differs.

What Happens Next?

1

30 minutes

Initial call

We analyse your process and identify the optimal starting point.

2

1 week

Discover

Mapping your decision logic. Rule sets documented, Decision Layer designed.

3

3-4 weeks

Build

Production agent in your infrastructure. Governance, audit trail, cert-ready from day 1.

4

12-18 months

Self-sufficient

Full access to source code, prompts and rule versions. No vendor lock-in.

Implement This Agent?

We assess your process landscape and show how this agent fits into your infrastructure.