  In conceptual modeling (CM), humans apply abstraction to represent excerpts
of reality for means of understanding and communication, and processing by
machines. Artificial Intelligence (AI) is applied to vast amounts of data to
automatically identify patterns or classify entities. While CM produces
comprehensible and explicit knowledge representations, the outcome of AI
algorithms often lacks these qualities while being able to extract knowledge
from large and unstructured representations. Recently, a trend toward
intertwining CM and AI emerged. This systematic mapping study shows how this
interdisciplinary research field is structured, which mutual benefits are
gained by the intertwining, and future research directions.
