The rapid advancements in artificial intelligence have begun reshaping public administration across Europe, and one of the most remarkable success stories comes from Germany’s Federal Employment Agency (Bundesagentur für Arbeit – BA). In recent years, the agency has faced rising workloads, increasing digital demands, and a structural need for greater efficiency — all while maintaining strict standards of privacy and operational accuracy. These pressures pushed the BA to explore next-generation automation technologies that could help streamline internal processes without compromising compliance or quality.
In partnership with Capgemini, the BA implemented a pioneering AI multi-agent system capable of automating the creation of Jira tickets — a task that had traditionally consumed thousands of hours of manual effort each year. This transformation is not only improving internal workflows but also setting a new standard for how public-sector institutions can embrace AI responsibly. The project represents a powerful example of innovation aligned with public administration needs, showing how AI can support — rather than replace — human-driven decision-making.
The Rising Pressure on Public Administrations to Modernize
Modern public agencies face unprecedented complexity. Digital transformation, increased citizen expectations, and limited staffing capacity have created operational bottlenecks. Germany’s Federal Employment Agency is no exception. With millions of documented IT processes each year, manually converting Requests for Change (RFCs) and user stories into structured Jira tickets had become inefficient and unsustainable.
The need for modernization was driven by multiple challenges:
- Rising digital workloads and limited staff availability.
- Growing administrative complexity in managing IT change requests.
- Increasing expectations for rapid, consistent, and error-free documentation.
- Strict confidentiality and data-protection requirements.
These pressures highlighted a strategic opportunity: adopting an AI-driven system that could significantly reduce manual work while maintaining accuracy and compliance.
Why the BA Chose AI Multi-Agent Technology
The BA and Capgemini recognized that a traditional automation tool would not be sufficient. Jira ticket creation is not a simple copy-paste task; it involves understanding context, extracting data, planning actions, and ensuring structural consistency. This complexity made the use of multi-agent AI technology ideal — a system where several specialized AI agents collaborate to complete tasks with human-like reasoning.
This approach offered several advantages:
- Agents could divide tasks into logical components such as analysis, planning, creation, and review.
- Complex RFCs could be broken down into manageable segments.
- Quality could be continuously monitored with a “human-in-the-loop” safety layer.
- The system could scale even as documentation volumes increased.
The result was a sophisticated yet flexible AI framework designed for real-world public-sector requirements.
Inside the Multi-Agent System: How It Works
The BA and Capgemini designed a multi-layered AI architecture made up of coordinated agents, each responsible for a specific step in the workflow. This creates a chain of intelligence that mirrors human reasoning but operates faster and more consistently.
1. Reader Agent
This agent scans RFCs and user stories, identifies relevant details, and extracts structured information such as requirements, objectives, and technical specifications.
- Extracts context from long documents.
- Identifies metadata, request types, and dependencies.
- Handles large RFCs while respecting LLM token limits.
2. Planner Agent
Once information is extracted, the planner agent determines the steps required to convert the request into a structured Jira ticket.
- Breaks tasks into logical components.
- Maps extracted information to Jira's required fields.
- Ensures accuracy and completeness before creation.
3. Creator Agent
This agent generates the actual Jira ticket content, including a polished title, description, categorization, and metadata.
- Writes clear and consistent ticket descriptions.
- Follows formatting standards and organizational guidelines.
- Assigns correct labels and categorization.
4. Reviewer Agent
Before human approval, a reviewer agent checks the output for quality, consistency, and duplicate entries.
- Ensures compliance with BA guidelines.
- Detects incomplete or conflicting information.
- Validates formatting for Jira compatibility.
This collaborative framework ensures each agent performs a specialized role, minimizing errors and maximizing clarity — while keeping human oversight at the center.
Privacy, Security, and On-Premises Architecture
Because the BA operates under strict German and EU data privacy laws, the AI solution needed to be entirely compliant, secure, and operated within the agency's own infrastructure. No cloud-based models or external data transfer were permitted.
To meet these requirements, the AI system uses:
- On-premises large language models (LLMs) such as Aleph Alpha, LLaMA, and Mistral.
- Local orchestration via CrewAI, an open-source AI coordination framework.
- Secure integration into the BA’s internal Jira environment.
- Strict data protection mechanisms ensuring all information stays within agency boundaries.
This privacy-first approach sets a new benchmark for public-sector AI adoption worldwide, demonstrating that automation can be both powerful and responsible.
The Impact: Real Efficiency Gains and Stronger Innovation Capacity
The multi-agent system is already delivering measurable benefits across the agency. What was once a slow, repetitive, and manual task is now handled automatically with high accuracy.
Key advantages include:
- Significant reduction in the time spent creating Jira tickets.
- Consistent, structured, and high-quality ticket content.
- Fewer errors and fewer duplicate entries.
- Ability to handle larger workloads without additional staffing.
- Improved employee satisfaction as staff shift toward strategic tasks.
The BA now has a stronger foundation for future innovation, having gained real-world experience in deploying and managing AI tools that complement — rather than replace — the human workforce.
Expanding the Use of AI Across Public Administration
The BA’s AI transformation is just the beginning. The success of the multi-agent system is encouraging the agency to expand AI integration into additional processes.
Planned future applications include:
- Automated document classification for large-scale administrative workflows.
- AI-assisted citizen communication tools.
- Workflow support for case management and public service requests.
- Enhanced analytical tools for policy development and strategic planning.
These expansions will help Germany continue building a modern, responsive, and efficient public sector capable of meeting increasing demands with limited resources.
The Strategic Importance of Human-AI Collaboration
A defining strength of the BA’s approach is its commitment to human oversight. Rather than using AI to replace staff, the agency uses automation to augment human capabilities, reduce manual fatigue, and enhance productivity.
The “human-in-the-loop” design ensures:
- Humans remain accountable for final decisions.
- AI outputs are reviewed before implementation.
- Errors are caught early, improving long-term system reliability.
- Staff can focus on higher-value, analytical work.
This model demonstrates a balanced path for responsible AI adoption in government operations.
Why This Project Is a Blueprint for Global Public Sector Innovation
Governments worldwide are exploring AI but face the same concerns: privacy, security, and trust. The BA’s success shows that these challenges can be addressed through careful design, responsible implementation, and collaborative oversight.
The project is now widely regarded as a benchmark due to:
- Its strict adherence to data privacy laws.
- A modular, scalable, and secure architecture.
- A proven ability to reduce workloads without reducing workforce value.
- An operational model that strengthens — not weakens — human control.
As more public institutions seek efficiency gains, this system offers a roadmap for deploying AI safely and effectively.
Conclusion: A New Era of Intelligent Public Administration
Germany’s Federal Employment Agency has demonstrated how AI can be thoughtfully integrated into public-sector operations, delivering measurable improvements while maintaining strict regulatory compliance. The BA’s multi-agent system is not just a technological achievement — it is a milestone in government modernization and a model for responsible AI implementation worldwide.
By reducing manual workloads, enhancing consistency, and empowering staff to focus on more meaningful tasks, this initiative marks the beginning of a new era where public administration is efficient, innovative, and citizen-centered.
FAQ
What is the purpose of the BA’s multi-agent AI system?
The system automates the conversion of Requests for Change and user stories into structured Jira tickets, reducing manual effort while improving accuracy and consistency.
Is the AI system fully autonomous?
No. It uses a human-in-the-loop model where staff review and approve all AI-generated tickets to ensure quality and accountability.
How does the BA ensure data privacy?
All AI processing occurs on-premises using secure, privacy-compliant models. No external cloud services or data transfers are involved.
What benefits has the BA reported so far?
The agency reports major reductions in manual work, improved ticket quality, higher efficiency, and increased innovation capacity.
Will the BA expand AI into other areas?
Yes. Planned expansions include document classification, workflow automation, and enhanced citizen communication tools.