The AI transformation , with its opportunities and risks, is also increasingly preoccupying public sector organizations. A current project shows how this path can be structured, made legally compliant, and designed with targeted change support.
Initial situation and challenges
Our client, an organization that awards grants, was under considerable cost pressure from higher-level ministries. The clear expectation was that processes should become more efficient and economical through the use of artificial intelligence.
At the same time, pressure came from the workforce itself. Many employees were already experimenting with tools such as ChatGPT or image generators on their own initiative and wanted to use them in their everyday work. The challenge was to ensure that AI did not emerge as shadow IT, but was introduced in a structured, legally compliant manner and in line with existing processes. The aim was to meet the efficiency requirements of clients while also making targeted use of employee motivation and commitment.
Project procedure
The starting point was a comprehensive AI readiness assessment. We analyzed the organization's maturity level across key dimensions: technology, legal, skills, culture, governance, process digitization, and data availability. The results served as the basis for a delta analysis of the desired target state.
The challenge: There was no explicitly formulated target vision, but there was a clear purpose. In order not to lose momentum in an additional strategy development process, we jointly developed four strategic options for the use of AI:
- Operational excellence,
- Ecosystem orientation,
- Focus on employees and
- Development of new business areas
The management decided to pursue operational excellence and focus on reducing the workload of employees through AI.
The AI use cases identified in the assessment were evaluated in terms of their benefits and the technical, procedural, and legal implementation costs. This resulted in a prioritized roadmap. The top use cases were worked out in detail for implementation over the next 100 days. In addition, the organization received recommendations on how it can further develop its AI maturity level in a targeted manner over a period of three years.
Lessons Learned
A key lesson learned from AI transformation is the importance of committed individuals. It takes employees who are passionate about driving the topic forward and exemplify it in their everyday work—even without external consulting.
The role of top management is equally crucial. AI transformation can only be successful in the long term if management has a fundamental understanding of what AI can achieve and where its limitations lie, and if it actively takes on the role of sponsor.
It is worthwhile to start with a few clearly prioritized use cases in order to avoid overwhelming yourself and to create something tangible and concrete ("small wins").
Two thoughts to take away
"AI is not a strategy—but AI can help achieve strategic goals."
"AI projects are not IT projects. They must be driven by the business departments and their understanding of business value."
Would you like to know how AI can specifically help your organization?
We would be happy to talk to you about useful areas of application, maturity levels, and first steps.
Get in touch with us here.