Effects of Artificial Intelligence on Enterprise Architectures - A Structured Literature Review

Artificial Intelligence (AI) is one of the key drivers of digital transformation and challenges enterprises to adapt to its various requirements. Many companies fail to implement AI applications or have significant trouble because of data or process requirements. The changes in a company resulting from the implementation of AI applications can vary from small data format changes over a restructuring of its application landscape to the implementation or deletion of whole business processes or roles. Thus, the implementation of AI applications can significantly impact a company’s enterprise architecture (EA). We argue that research could facilitate the adoption of AI and help to preserve AI projects from failing. To determine what further research is necessary, this paper seeks to give an overview of the current state-of-the-art of research on the effects of AI applications on EA. For this purpose, we performed a structured literature review (SLR), formulating inclusion and exclusion criteria, developing several search strings, applying them to four scientific databases, performing a forward and backwards search and summarizing the key findings. The (1) performance of the literature review and the (2) discussion of its findings are the main contributions of this paper, identifying a research gap as no concrete research about the effects of AI applications on enterprise architectures could be found. However, a handful of papers in the area of AI and EAM are discovered that endorse the need for further research.