Technology transfer deals with the exchange of technological knowledge between organizations, particularly between research organizations and industry. Efficient technology transfer is an important pillar of economic growth and the social utilization of research results. As part of the ongoing digitalization of academia and industry, artificial intelligence is currently considered to have the greatest transformation potential. Accordingly, it is obvious to conduct research at the interface between technology transfer and artificial intelligence. The current state of scientific literature on this interface is fragmented into specific individual studies on sub-areas of technology transfer, while a broad overview of key concepts is lacking. Furthermore, it is unclear how the relationship between technology transfer and artificial intelligence is structured in these key concepts. To close this gap, a systematic literature review according to Webster & Watson (2002) was conducted. The systematic literature search revealed eleven different key concepts at the interface between technology transfer and artificial intelligence, which can be divided into two categories. In the first category, AI is the object to be transferred over diverse transfer mechanisms. In the second category, AI assists in different steps of the technology transfer process. As scientific implication, this study provides a basic framework that serves scientists as a starting point for further research. As practical implication, it supports practitioners and policy makers to identify transfer mechanisms through which the economy and society can benefit from AI research. This study also provides initial approaches on how technology transfer can be improved by AI.