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EU AI Act III(4)(b): High Risk Q4

Promotion Process Agent

Structured promotion governance - from eligibility check to budget impact.

Administers the promotion process: eligibility checks, budget approval, pay band review, and documentation. EU AI Act high-risk applies.

Analyse your process
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Assessment

Agent Readiness 54-61%
Governance Complexity 74-81%
Economic Impact 51-58%
Lighthouse Effect 66-73%
Implementation Complexity 46-53%
Transaction Volume Yearly

What This Agent Does

Promotion decisions are among the most consequential in HR - they affect compensation, career trajectory, team dynamics, and organisational culture. While the promotion decision itself is fundamentally human, the process surrounding it involves significant administrative complexity: eligibility checking against time-in-grade rules and performance requirements, documentation assembly, budget impact calculation, multi-level approval workflows, pay range validation, and (where applicable) works council notification. The Promotion Process Agent manages this administrative process. It verifies that promotion candidates meet eligibility criteria, assembles the required documentation (performance reviews, manager recommendation, business justification), calculates the budget and compensation impact, routes the case through the required approval chain, validates that the new compensation falls within the correct pay range, and generates the documentation required for audit and regulatory compliance. This agent is classified as high-risk under the EU AI Act (Annex III, Section 4(b)) because it participates in decisions about career progression that affect employment conditions. The agent administers - it does not decide who gets promoted.

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 promotion recommendation Intake manager recommendation with business justification Human

Human recommendation initiates the process

Decision Record

Decider ID and role
Decision rationale
Timestamp and context

Challengeable: Yes - via manager, works council, or formal objection process.

Verify eligibility Check time-in-grade, performance requirements, and policy compliance Rules Engine

Deterministic rules per promotion policy

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.

Assemble documentation Compile performance reviews, recommendations, and justifications AI Agent

Automated document assembly from existing records

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.

Calculate compensation impact Determine salary change, new band position, and budget impact Rules Engine

Calculation rules from compensation structure and grade mapping

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.

Validate pay range Confirm new compensation falls within target grade pay range Rules Engine

Range check against defined pay structure

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 for approval Send promotion case through required approval chain Rules Engine

Approval chain rules per promotion type and organisational level

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.

Obtain approvals Multi-level approval (next-level manager, HR, budget owner) Human

Human approvals required at each level

Decision Record

Decider ID and role
Decision rationale
Timestamp and context

Challengeable: Yes - via manager, works council, or formal objection process.

Notify works council Inform works council where co-determination applies Rules Engine

Automated notification per works council agreement 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.

Generate promotion documentation Create promotion letter, contract amendment, and payroll instruction AI Agent

Automated document generation from approved promotion data

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 systems Execute changes in HR, payroll, and organisational systems AI Agent

Automated downstream updates after approval completion

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

  • Promotion policy with eligibility criteria
  • Grade and pay range structure
  • Performance review documentation (ideally from Performance Review Documentation Agent)
  • Multi-level approval workflow infrastructure
  • Budget tracking and impact calculation capability
  • Works council notification process where applicable
  • EU AI Act conformity assessment for high-risk classification
  • Decision logging infrastructure for audit trail

Governance Notes

EU AI Act III(4)(b): High Risk
Classified as high-risk under the EU AI Act, Annex III, Section 4(b) - the agent participates in decisions about career progression. Conformity assessment is mandatory. The agent administers the process but does not make promotion decisions. Works council co-determination rights apply to promotion processes in many jurisdictions. Every eligibility check, approval, and system change must be logged for audit trail compliance. The Pay Transparency Directive may create additional requirements for documenting promotion criteria. The Decision Layer decomposes every process into individual decision steps and defines for each: Human, Rules Engine, or AI Agent. Every decision is documented in a complete decision record. Affected employees can understand and challenge any automated decision.

Infrastructure Contribution

The Promotion Process Agent builds the multi-level approval and eligibility verification infrastructure that supports any agent managing career-affecting processes. The pattern of human decision with automated eligibility checking and documentation is reusable across the talent management domain. 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.

Promotion Process 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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Related Pages

Decision Layer
Governance layer between AI agent and target system. Every decision documented and challengeable.
EU AI Act
High-risk requirements: risk management, transparency, human oversight.
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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Back to Catalog

Frequently Asked Questions

Does the agent decide who gets promoted?

No. Managers recommend promotions. The agent verifies eligibility, assembles documentation, calculates impact, and manages the approval workflow. The promotion decision is human at every level.

What happens when a promotion candidate does not meet eligibility criteria?

The agent flags the specific eligibility gap and returns the case to the recommending manager. Some eligibility gaps may be waivable through an exception process - the agent routes these for the appropriate exception approval.

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.