Whether in traffic control, robotics or speech recognition – artificial intelligence (AI) can now be found in many different areas of application and enables large data sets to be analyzed or self-learning programs to be developed. This also benefits small and medium-sized enterprises (SMEs) from rural regions, which can work more cost-effectively and efficiently with AI. Vanessa Cann, Managing Director of KI Bundesverband e.V., emphasizes the long-term potential of AI for SMEs and the infrastructural opportunities of AI applications in the areas of health or mobility in rural areas in the aconium interview “5 answers”.
aconium: The digital transformation using AI offers particular opportunities for Germany. How do you think this could also strengthen rural regions?
Vanessa Cann: Rural areas in Germany are characterized by strong SMEs that are currently facing a major challenge: They have to master the digital transformation and rethink products and processes digitally and more efficiently.
Made in Germany – that has always been a globally recognized quality feature. This can also be the case in the digital world if our SMEs reinvent themselves through the focused use of artificial intelligence.
Life in rural areas can also benefit from AI. A current example is telemedicine or automatic diagnoses and answers to medical questions that promise quick help – even in regions where the nearest specialist is a little further away.
aconium: In which areas has artificial intelligence already contributed to the further development of rural areas?
Vanessa Cann: Unfortunately, artificial intelligence has hardly been used in rural areas to date. A nationwide network expansion can create new opportunities here.
Secondly, businesses and companies in rural areas still make far too little use of available AI technologies. I currently see three hurdles here. Firstly, there is simply a lack of knowledge about the benefits of AI. This is where most fail. Secondly, money is often not made available for long-term projects after a pilot project. And thirdly, there is a lack of talent and specialists in rural regions who could implement and drive forward AI projects for companies.
aconium: How can equal living conditions between urban and rural areas be created with the help of artificial intelligence?
Vanessa Cann: Artificial intelligence can solve the infrastructure problems of rural regions in particular. Instead of having to wait a long time for the bus, people could be transported from A to B at the touch of a button using demand-responsive services. Intelligent route planning for local public transport can replace standard routes by always offering mobility where it is needed.
But there is also a lot of potential in the area of health and care in terms of diagnosis, prognosis and prevention, which can reduce visits to the doctor and counteract the problem of poor medical care in rural areas.
aconium: Which ideas and visions from the field of AI do you think have the most potential to strengthen rural areas?
Vanessa Cann: Germany is characterized by many “hidden champions” – SMEs from rural regions that are world market leaders in their niche. Many AI companies are focusing on helping precisely these SMEs to remain a “champion” in the digital age through digitalization and the clever use of AI.
The risk of falling behind as a result of digitalization has never been greater. At the same time, the opportunity to catch up as quickly as possible through AI has never been greater.
aconium: What wishes do you have for optimal AI-based applications?
Vanessa Cann: Broadband expansion is absolutely fundamental for a functioning digital infrastructure on the basis of which AI applications can be used across the board. Otherwise, the use of AI products in rural areas will not succeed.
At the same time, knowledge gaps and fears need to be reduced. Many SMEs do not take advantage of opportunities to achieve major efficiency gains and cost savings through AI because they do not understand the technology and its potential applications. Currently, only one in seven companies invests in AI projects. That is not enough.
And finally, more clarity is needed with regard to data protection. After all, AI thrives on learning from data. A lot of data currently remains unused because companies are afraid to share theirs. By doing so, we are cutting ourselves in two, because then the systems will be developed and trained in other countries and that would be a wasted opportunity.