Medium-sized cities are the biggest problem

Cities and regions are only smart if they use AI intelligently and innovatively – and do so under very different starting conditions. The panel discussion ‘AI for cities and rural areas: different starts, joint design’, opened by a keynote speech by Björn Niehaves, showed what these conditions currently look like in local authorities.

Niehaves is a professor of computer science at the University of Bremen, where he heads the research group ‘Digital Transformation of Public Services,’ which recently surveyed 44,290 public administration employees from more than 30 large, medium-sized and small cities and counties on the use of AI. He presented his core theses on the extent to which the use of AI can be shaped jointly – and who is leading the way.

• 80 per cent of all AI products and projects are relevant in some form in all municipalities, whether urban or rural.
• The differences within the categories are greater than those between urban and rural areas. For example, the situation in large city A is significantly different from that in large city B, but similar to that in medium-sized city C and district D.
• Integrated data management, or the lack thereof, is a problem almost everywhere.
• More resources alone are not decisive for success. It depends on how the money is spent.
• The variance among medium-sized towns is greater than among districts and large cities. Both the best and the worst performers in terms of AI are medium-sized towns.
• Small towns tend to lag behind in terms of process, change and data management for AI use that goes deeper than ChatGPT.
• Inter-municipal cooperation is always a good idea when it comes to AI – whether in urban or rural areas. Cooperation saves both financial and human resources.
• A clear AI strategy is essential.

Relieving employees of their ‘pain points’

Sabrina Donner brought her experience with AI from Germany's smallest district to the panel. She heads the digitalisation department at the Lüchow-Dannenberg district, where ten AI projects are already underway, two of which were developed specifically for local needs. They started with the ‘pain points’, the tasks that all employees complain about in one way or another – such as taking minutes at political committee meetings. ‘We take that off their hands with AI.’ What used to take two to three working days can now be done in half a day thanks to AI. This shows employees that we want to relieve them of some of their workload, not eliminate their jobs.

Exchange and cooperation with other municipalities is a key focus for Dorothea Prell, Smart City Officer for the city of Jena. To develop a multifunctional chat system for communication within the administration, but also between citizens and the administration, her city is working with the municipality of Süderbrarup in Schleswig-Holstein on an open source-based basic system that can also be used by other municipalities in the future. Prell advocated for local AI competence centres, for example in collaboration with universities: ‘Find allies, network.’

Dr Annika Busse also contributed practical examples to the panel discussion. She is the acting CIO of the Free and Hanseatic City of Hamburg and is responsible for the city's IT management. More than 50 AI projects are currently active in Hamburg in various stages – from pilot to full operation. AI supports the water police, for example, in detecting undeclared dangerous goods in containers in the port. The Hamburg ChatGPT version LLMoin is designed to relieve employees of the burden of text entry. ‘Using it is also a good way to show employees that they don't need to be afraid of AI,’ says Busse.