Reflections and Takeaways from BMFTR's Mittlestand Forum

November 12, 2025

This week, I attended the Mittelstandsforum 2025 in Berlin, a flagship event organised by the German Federal Ministry of Research, Technology and Space (BMFTR). Focusing on funded innovation projects for SMEs (KMUs) under the programmes “KMU‑innovativ: IKT” and “KI4KMU”, the two-day forum brought together research institutions, technology providers, and SME end-users. It was a fantastic convergence of project results, networking opportunities, idea generation, and expert consultations via four dedicated AI-Service-Centres.

The Backbone of the German Economy

A recurring theme throughout the forum was the pivotal role that SMEs play as the backbone of the German economy. Federal funding agencies like the BMFTR are keenly focused on providing these enterprises with opportunities to grow, innovate, and develop new competencies. In today’s landscape, one competency stands out as a true game-changer: Artificial Intelligence. AI is widely seen as a critical technology that will shape the future of both the German and the broader European economy.

The State of AI Adoption: Insights from ZEW

A particularly insightful session was a presentation by Irene Bert from the ZEW- Leibniz Centre for European Economic Research, who shared findings from a recent survey on AI adoption in Germany.

The study revealed that approximately 18% of German SMEs are currently using AI in their workflows. While this shows good progress, it places Germany in the middle of the pack compared to other European countries, with nations like Denmark showing the highest rates of adoption. The survey also highlighted that within Germany, larger corporations have a slightly higher adoption rate, indicating that SMEs are still lagging behind.

So, what’s holding them back? The ZEW study identified several key roadblocks, or Hemmnisse:

• Uncertainty: A primary obstacle is the uncertainty surrounding the return on investment and the tangible benefits of implementing AI.
• Lack of Know-how and Specialists: Many companies struggle with a lack of in-house expertise and find it difficult to hire skilled AI professionals.
• Data Accessibility: A significant challenge is the lack of access to high-quality, relevant data required to train and implement effective AI models.
• High Investment Costs: The initial financial outlay for AI implementation can be prohibitive for smaller companies.

Our Contribution: The KIKERP Project

The forum was also a great opportunity to share our own research during a lively and engaging poster session. I presented our project, KIKERP, which is a prime example of practice-oriented, BMFTR-funded research aimed at strengthening the circular economy.

The KIKERP project focuses on using AI to support the refurbishment and reuse of electrical appliances. Our AI-powered assistance system helps the end users and the employees in the remanufacturing process to quickly and accurately identify, classify, and evaluate used devices. By leveraging a dataset of over 30,000 images, our system can classify more than 5,000 different types of products with 97% accuracy, streamlining the circular economy process. This project demonstrates how targeted AI applications can solve practical challenges in sectors like manufacturing and logistics.

You can learn more about our research in this recent interview.

A Hub of Diverse Innovation

One of my key observations was the incredible diversity of AI research and application on display. The projects spanned numerous domains, showcasing how AI is being tailored to solve specific industry challenges in areas like automotive, medicine, transportation, and education.

This diversity was reflected in how the posters and presentations were structured. All projects were grouped into four distinct categories, which helped to organise the discussions and highlight key areas of innovation:

• Arbeit und Gesellschaft im Wandel (Work and Society in Transition)
• Digitalisierte und vernetzte Produktion (Digitized and Networked Production)
• Sichere und nachhaltige Systeme (Secure and Sustainable Systems)
• Wissen und Mehrwert aus Daten (Knowledge and Added Value from Data)

A Forum for Connection and Collaboration

Beyond the formal talks, the poster session was a hub of discussion and networking. It was an invaluable experience to connect with a diverse group of people from funding agencies, universities, and fellow SMEs. The exchange of ideas was incredible, and these conversations are essential for bridging the gap between research and practical application.

Events like the Mittelstand-Forum are crucial. They shed light on the current challenges and opportunities and create a space for the collaboration needed to drive the German economy forward. I left feeling inspired and optimistic about the future of AI in the German Mittelstand.```

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