  This paper presents multi- and interdisciplinary approaches for finding the
appropriate AI technologies for research information. Professional research
information management (RIM) is becoming increasingly important as an expressly
data-driven tool for researchers. It is not only the basis of scientific
knowledge processes, but also related to other data. A concept and a process
model of the elementary phases from the start of the project to the ongoing
operation of the AI methods in the RIM is presented, portraying the
implementation of an AI project, meant to enable universities and research
institutions to support their researchers in dealing with incorrect and
incomplete research information, while it is being stored in their RIMs. Our
aim is to show how research information harmonizes with the challenges of data
literacy and data quality issues, related to AI, also wanting to underline that
any project can be successful if the research institutions and various
departments of universities, involved work together and appropriate support is
offered to improve research information and data management.
