WG 4: Business Model Innovations
Self-learning systems convert data to knowledge. They use the exponentially growing amount of data in order to make products and services “smart”. With the help of machine learning patterns can be detected and identified from various data sets and predictions can be made. Entirely new data- and AI-based business models will emerge. The customer will remain at the core of all efforts. He or she will frequently be informed about products and services according to his or her individual needs. Small businesses are often not able to implement new data-based business models on their own. Therefore, it is crucial for them to cooperate with other companies on a larger scale.
Topics and Organisation of the Working Group
The working group identifies and analyses new business models on the basis of artificial intelligence as well as the economic potential of self-learning systems. It provides impetus in particular for the application-oriented working groups.
Members of the Working Group
- Prof. Dr. Irene Bertschek
- ZEW – Leibniz Centre for European Economic Research
- Prof. Dr. Michael Dowling
- Universität Regensburg
- Prof. Dr.-Ing. Roman Dumitrescu
- Fraunhofer Institute for Mechatronic Systems Design
- Prof. Dr. Svenja Falk
- Accenture Services
- Stephanie Fischer
- datanizing GmbH
- Dr. Christian Friege
- Cewe Foundation
- Christian Gülpen
- RWTH Aachen
- Dr. Andreas Liebl
- UnternehmerTUM GmbH (applied.AI)
- Olga Mordvinova
- incontext.technology GmbH
- Prof. Dr.-Ing. Astrid Nieße
- Leibniz University Hannover
- Prof. Dr. Alexander Pflaum
- Fraunhofer SCS
- Prof. Dr. Frank Thomas Piller
- RWTH Aachen
- Dr. rer. nat. Uwe Riss
- FHS St. Gallen – University of Applied Sciences
- Fabian Schmidt
- Software AG
- Dr. Markus Schnell
- Infineon Technologies AG
- Barbara Susec
- Prof. Dr. Orestis Terzidis
- Karlsruhe Institute of Technology (KIT)
- Iris Wolf
- IG BCE
We have received written consent from the listed persons for the publication of their data in accordance with the DSGVO. This list of members is an excerpt and will be completed continuously.
Key Questions for the Working Group
- How do self-learning systems change cost structures in companies and business (e.g. skilled employees, know-how, efficiency and information benefits)?
- How can redeeming structures change when it comes to new ways of customer loyalty and net product concerning smart products and services?
- Which new business models can occur for small and larger companies?
- Are there any new forms of cooperation that are necessary for a successful usage (e.g. platforms and eco systems)?
Conclusions and Contributions of the Working Group
- New Business Models using Artificial Intelligence
- Year of publication: 2019
- Artificial Intelligence (AI) has recently made breakthroughs in very different areas of application. This progress has been made possible by advances in algorithms, particularly in the case of Machine Learning (ML) and Deep Learning (DL), coupled with the availability of very large volumes of data (Big Data) and advances in fast, parallel computing (Kersting, Tresp 2019). Applications that just a few years ago seemed to be far out of reach are now already – or are soon to become – part of our daily lives.
- Contact: Birgit Obermeier / Linda Treugut
Coordination of the Working Group at the Managing Office: Dr. Thomas Schmidt