AI in public administration: Why technology alone is not enough

Artificial intelligence is no longer a topic for the future in public administration. Political requirements, rising citizen expectations, and a growing shortage of skilled workers are increasing the pressure to redesign administrative processes. At the same time, tasks and case numbers are growing, while qualified personnel are becoming increasingly difficult to recruit.

AI promises to ease the burden precisely where time and capacity are lacking today: in file preparation, research, text work, or the preliminary review of processes. The potential is real and can make a tangible contribution to overcoming these challenges. Nevertheless, the hoped-for effect often fails to materialize in everyday work. In the worst case, it can even lead to frustration and additional effort.

The reason for this rarely lies in the technology. There is often a lack of clear guidelines for its use: Who is responsible? What data does the AI work with? How does it fit into existing processes and legal requirements? Do all employees have the necessary knowledge and skills to use it safely?

As long as these questions remain unanswered, AI will remain an experiment—technically interesting, but not firmly established in the organization and without broad acceptance among employees.

Many administrations have already launched or completed AI pilot projects. Chatbots answer standard queries, documents are classified automatically, and texts are pre-formulated. Technically, these solutions often work well. Nevertheless, key questions remain unanswered. As a result, the leap to regular operation is rarely successful.

In practice, similar challenges arise time and again:

• Responsibilities between departments, IT, and data protection are not clearly defined.
• Data is available but cannot be used in the required quality or structure.
• Processes have evolved over time and have limited potential for automation.
• Employees are unsure how and for what purposes AI may be used.

The aspect of security is particularly sensitive. Administrative actions require data protection, traceability, and audit compliance. However, many AI projects do not adequately answer key questions: Where is the data processed? What data is included? How transparent are the results? And what consequences does this have for my own work?

This uncertainty not only affects acceptance, but also directly influences usage. If employees are concerned about violating legal requirements, cannot understand the role of AI in the overall context, or cannot explain decisions later on, they will refrain from using it when in doubt – even if the solution would make sense from a technical standpoint and could offer tangible benefits.

Secure AI use in closed structures

One of the biggest challenges is the use of AI within closed public authority infrastructure. Open, freely learning systems can only be used to a limited extent in public administration. Data protection, confidentiality, and compliance set clear limits.

Three questions are crucial here:

1. Data basis: Does the AI work exclusively with validated, legally permissible data?
2. Processing location: Does processing take place in an internal government environment, such as on-premises or in a sovereign cloud?
3. Transparency: Are the results traceable, explainable, and audit-proof?

These points are decisive for trust. Employees will only use AI if they are sure that they are acting in compliance with regulations and within the existing chains of responsibility.

AI as relief in personnel shortages

At the same time, the administration is facing a structural personnel problem. Demographic change, increasing tasks, and lengthy recruitment procedures are noticeably exacerbating the situation.

AI can provide targeted support here. Not as a replacement, but as a relief:

• Automation of repetitive tasks
• Support with research, classification, and preliminary review
• Faster processing with consistent quality
• Securing knowledge despite staff turnover

This allows more to be achieved with limited resources without compromising legal certainty or quality.

AI is changing working methods and role models. Research, pre-structuring, and initial drafts are partly shifting to systems. Professional responsibility remains – but the path to decision-making is changing.

This shift requires guidance. A tension arises between proven practices and new possibilities, which should be actively addressed. Managers play a central role in this. They provide direction by clearly defining what AI is used for – and what it is deliberately not used for. They create guidelines, prioritize suitable use cases, and signal that learning and experimentation within clear rules are desirable.

At the same time, it is important to make it clear that this transition is a process. It does not happen overnight. Just as technical structures are built up step by step, the safe use of AI in everyday work also develops step by step.

Successful AI projects involve employees, specialist departments, IT, and data protection at an early stage. Not to complicate processes, but to clearly define responsibilities and promote acceptance from the outset. AI is not simply “rolled out,” but rather translated into practice together – and sustainably anchored in everyday work.
 

The benefits of AI are determined in everyday work. A solution only becomes effective when employees use it as a matter of course and experience it as genuine support. This requires clearly defined use cases that provide noticeable relief.

The following have proven effective, for example:

• File preparation and pre-structuring
• Drafting texts based on technical specifications
• Research and structured summarization of internal information
• Preliminary review of incoming applications or documents

Clear rules of use are equally important. Which data may be used? How should results be checked? Who bears technical responsibility? And what role do I play in the new process? Such guidelines provide security in dealing with the technology. In combination with practical training and the active participation of employees, trust is created – and with it the basis for sustainable use.

Successful administrations take a step-by-step approach. They start with selected use cases, measure the impact, and scale up in a targeted manner. In this way, AI develops from a project to a tool – and from a tool to a natural part of everyday work.

Artificial intelligence can make public administration more efficient and effective. However, its success is not determined by technology alone, but by the targeted involvement of employees – supported by leadership, culture, and consistent user adoption.

Security, traceability, and clear responsibility form the basis of any use. AI unfolds its added value where employees understand how it works, what it is used for, and how it specifically supports their own daily work.

In this way, AI is not perceived as a risk or a threat to one's own job, but as a tool that reduces workload and ensures quality. Where learning and reflective application are part of daily work, technological innovation becomes sustainable progress for the organization.