How AI improves casework in the public sector
Responsible AI in public sector casework is not about replacing the caseworker. It is about better access to approved knowledge — with control, transparency and clear ownership.
Pressure on public sector casework is rising.
Case volumes are growing. Citizens and businesses expect faster answers. Staff must navigate complex rules, guidance and internal procedures. And at the same time, there is a clear requirement that decisions must be correct, consistent and lawful.
That is why AI is often mentioned as a possible solution.
But in a public sector context, the question is not simply whether AI can make the work faster. The question is whether AI can be used responsibly.
Public authorities cannot work with systems that answer from unknown sources, invent explanations or create uncertainty about the basis for decisions. AI in casework requires control, transparency and a clear knowledge foundation.
That is why AI should not be understood as a replacement for the caseworker.
The right application is more practical: AI can help the caseworker find relevant knowledge faster, understand current practice and prepare better responses — while responsibility remains with the authority and the professional employee.
What do we actually mean by AI for casework?
AI for casework is not a robot that makes decisions.
Nor should it be.
In a public authority, decisions must continue to be made on a professional, legal and administrative basis. AI can support the work, but it must not remove the authority's responsibility or make the basis for decisions unclear.
That is why the most relevant use of AI in casework is often as knowledge support.
This could, for example, be:
- finding relevant guidance faster
- pointing to current internal procedures
- providing an overview of complex rules
- helping draft wording for standard responses
- making it easier to work from approved and up-to-date knowledge
The point is not that AI should decide.
The point is that the caseworker should spend less time searching and more time assessing.
| Misconception | More responsible application |
|---|---|
| AI makes decisions | AI helps the caseworker find relevant knowledge |
| AI replaces professional judgement | AI supports professional judgement |
| AI answers freely from the internet | AI answers from approved sources |
| AI makes the process opaque | AI makes sources and the knowledge basis more accessible |
That is the difference between uncontrolled AI and AI as a responsible part of the authority's knowledge work.
The concrete bottlenecks in public sector casework
Long case processing times are rarely due to a single factor.
But many bottlenecks share the same root: it takes too long to find the right knowledge.
Public sector caseworkers often work with knowledge spread across legislation, executive orders, guidance, internal notes, previous practice, emails and case systems. This makes the work complex — especially when rules change, or when several departments must work to the same interpretation.
The typical problems look like this:
| Bottleneck | What happens in practice? | Consequence |
|---|---|---|
| Knowledge is scattered | The caseworker searches multiple sources | Case processing time increases |
| Knowledge is hard to interpret | Rules and guidance require professional clarification | More cases are escalated |
| Experienced colleagues become the knowledge bank | New employees ask the same key people | Bottlenecks and interruptions |
| Practice varies | Different staff use different sources | Less consistency in responses and decisions |
| Knowledge has no clear owner | No one knows which version is current | Uncertainty and double-checking |
This is not a question of caseworkers working slowly.
It is a structural knowledge problem.
When the right knowledge is hard to find, casework becomes dependent on experience, internal shortcuts and informal clarifications. That makes the organisation vulnerable — especially during onboarding, busy periods, legislative changes and organisational shifts.
What AI can — and cannot — do in a public authority
AI cannot take over the authority's responsibility.
It cannot stand alone as the basis for a decision. It cannot replace a specific assessment. And it should not be used as a black box where the caseworker cannot see why an answer is given.
But AI can solve some very concrete problems in casework.
It can help find the relevant knowledge faster. It can create an overview of large volumes of documentation. It can suggest wording for standard responses. And it can make it easier for new employees to work from the same approved foundation as experienced colleagues.
That makes AI relevant in three parts of casework:
| Task | How AI can help | What AI should not do |
|---|---|---|
| Information retrieval | Find relevant guidance, practice and procedure | Make up answers without a source |
| Case preparation | Create an overview and suggest next steps | Make the decision |
| Communication | Suggest draft responses based on approved knowledge | Send decisions without professional review |
The crucial point is that the AI operates within controlled boundaries.
When AI is used as a search and drafting assistant on top of an approved knowledge base, it becomes a practical tool for the caseworker — not a replacement for the caseworker's judgement.
This is also where Responza's approach becomes relevant. The AI helps the employee find, understand and use the organisation's approved knowledge — without losing control of what answers are based on.
Governance and compliance — the decisive prerequisite
The public sector cannot use AI the same way one uses an open chatbot.
In a public authority, it is not enough for an answer to sound right. It must be explainable, controllable and grounded in approved sources.
That is why governance is not an extra layer on top of the AI solution.
It is the very prerequisite.
Governance in AI for casework is mainly about four things:
- The AI must only answer from approved and verified knowledge.
- The caseworker must be able to see which sources an answer is based on.
- There must be clear ownership of the knowledge the AI uses.
- There must be processes for updating, approval and quality assurance.
Without this, the risks that public organisations are rightly concerned about arise: incorrect answers, unclear sources, lack of traceability and uncertainty about the basis for decisions.
With the right knowledge foundation, AI can instead be used in a more controlled way.
| Without governance | With governance |
|---|---|
| AI can answer from unknown sources | AI answers from approved knowledge |
| Sources are unclear | Sources can be traced |
| Answers can vary unpredictably | Answers are based on the same knowledge foundation |
| No one knows who owns the content | There is clear responsibility for updates |
| Employees lose trust in the system | Employees can verify and use the answer |
For public authorities, this is the difference between AI as a risk and AI as a responsible working tool.
Examples from public sector practice
AI for casework does not need to start as a multi-year transformation project.
Responza is already used in public and publicly regulated organisations. What they have in common is not that AI takes over casework. What they have in common is that employees get better access to the knowledge they need to work faster, more consistently and in a more controlled way.
Experience also shows that the path to value can look different.
Some organisations can get started quickly if the scope is clear and the knowledge foundation is already defined. Others have longer implementation processes because the subject area is complex, or because the solution must be anchored across several units, processes and data sources.
For some, the benefit lies mainly in faster access to knowledge. For others, it lies in more consistent answers, shorter training time or less dependence on key people. And in some cases, the biggest business case lies in AI-supported responses, where employees can prepare fast, correct and controlled answers based on approved knowledge.
That is precisely the point: responsible AI in the public sector is not about one particular use case. It is about creating a controlled knowledge foundation on which AI can operate safely.
Responsible AI in the public sector is not about automating the authority's responsibility. It is about giving employees faster access to the knowledge they already need to work from.
That is why the practical way forward is rarely to start with “AI across the entire organisation”. It is to start with a specific area, a clear knowledge foundation and a clear business case.
How an authority gets started with AI for casework
The hardest part of AI for casework is rarely the AI itself.
The hardest part is getting the knowledge foundation in order.
If knowledge today is scattered across documents, drives, emails, case systems and key people, you should not start by “adding AI”. You should start by finding out what knowledge caseworkers actually use.
A practical approach can look like this:
1. Map the knowledge caseworkers use most
Start with the areas where caseworkers are often unsure, ask colleagues or spend a long time finding answers.
This could be guidance, internal procedures, standard responses, escalation rules, legal interpretations or practice notes.
2. Gather and structure the knowledge foundation
Once the most important knowledge has been identified, it must be gathered and structured so it can be used in everyday work.
It is not about documenting everything at once. It is about starting with the areas where better access to knowledge will make the biggest difference.
3. Implement AI on top of approved knowledge
AI should only be introduced once there is clarity about what it should answer from.
This makes the solution more controlled. The caseworker gets help finding and drafting answers, but the answers are based on the authority's own approved sources.
4. Establish governance and ownership
A knowledge platform only works if someone owns the content.
It must therefore be clear who may update knowledge, who approves changes, and how outdated versions are removed from everyday use.
5. Start narrow — and then scale
AI for casework does not need to start as a heavy IT project.
An authority can start with a defined area, document the effect and then expand the solution to more case types or departments.
According to Responza, the solution can be implemented in under 3 months. This makes it possible to get started without making the project bigger than necessary — provided the knowledge foundation and ownership are prioritised from the start.
AI in casework is about better access to knowledge
AI in public sector casework should not be about replacing the caseworker.
It should be about supporting the caseworker.
When AI is used responsibly, it can help employees find relevant knowledge faster, work more consistently and spend less time searching through complex documents and internal sources.
Key takeaways
- 1AI for casework should support — not replace — professional judgement.
- 2Responsible AI requires a structured knowledge foundation, clear sources and strong governance.
- 3The impact depends on whether the solution is built on approved knowledge, clear ownership and a specific business case.
Frequently asked questions
Can AI be used legally in public sector casework in Denmark?
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AI can be used in public sector casework if its use complies with applicable legislation, data protection rules and administrative law requirements. What matters is what the AI is used for. AI as support for information retrieval and drafting is different from AI that makes decisions automatically.
What is the difference between AI for casework and automated casework?
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AI for casework can help the caseworker find knowledge, create an overview and draft responses. Automated casework means a system fully or partially makes decisions in the case. In a public authority, the difference matters because responsibility, documentation and legal basis must be clear.
How do you ensure AI does not give incorrect answers in a public authority?
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You reduce the risk by ensuring the AI only answers from approved and verified sources. The caseworker must be able to see the source behind an answer, and there must be clear processes for updating and quality assurance. AI should support the assessment, not replace it.
Which public organisations are already using AI and knowledge platforms?
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Responza is already used in public and publicly regulated organisations. Experience shows the value can look different from organisation to organisation: faster access to knowledge, more consistent answers, shorter training time or strong business cases for AI-supported responses. What they have in common is that the solution is built on approved knowledge, clear ownership and controlled use of AI.
What does it take to implement AI in an agency or municipality?
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First and foremost, it requires a clear knowledge foundation. The authority must know which sources the AI may use, who owns the content, and how knowledge is updated. AI can then be implemented in a defined scope, tested in practice and scaled to more areas.
Martine Koehler Andersen
Founder & CEO
Martine skriver om ledelse, vidensgovernance, AI og organisatorisk kvalitet i kundeservice og sagsbehandling. Hun har mere end 20 års erfaring med at opbygge service- og vidensmiljøer i komplekse organisationer i Danmark, Europa og USA.
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