On Oktober 14 at 10:00, Jack Rittelmeyer will defend his PhD thesis in Konrad-Zuse-Haus, room 001. The thesis' topic is „Development and Evaluation of a Morphological Box for Artificial Intelligence Solution Integration“.
Abstract
Even in the area of generative Artificial Intelligence (AI), many AI integration projects still fail, and companies struggle to successfully integrate AI applications in their businesses. Due to the hype of AI since the rise of solutions like OpenAI’s ChatGPT and Microsoft Copilot, the number of companies wanting to benefit from the technology increased significantly. However, the lack of knowledge about AI and the lack of awareness for the complexity of AI applications and their integration into existing business structures, processes and applications lead to the failure or rising costs of many integration projects. Furthermore, discussions with companies and a Structured Literature Review (SLR) showed the lack of a
suitable artifact that provides the most important aspects for successfull AI introduction in businesses.
This dissertation uses the Design Science Research paradigm to develop an artifact that summarizes
the different facets of AI and of its integration in companies: the Morphological Box (MB) for AI solution integration. The main goal of a MB is to break down a wide and compley problem into many smaller problems that are then easier to understand and to solve. The author of this dissertation argues that this strategy can be adopted for AI with the goal to break down the overall topic of AI integration in companies into its most important features and provide the user of the artifact with possible values for each feature. The MB was constructed and refined through an iterative process of five evaluation episodes, including expert interviews and discussions and two surveys, as well as by applying it in different business and scientific use cases. Furthermore, the use cases demonstrate the variety of application potentials of the artifact and benefits of using it, besides the support for AI solution
integration in companies.
The main contribution of this thesis is the evaluated MB for AI solution integration and the demonstration of its application possibilities and benefits in business and science.