Artificial intelligence (AI) carries great potential for data-based process improvements in intralogistics of manufacturing companies. This paper provides a comprehensive catalog of ten AI use cases structured along the most relevant intralogistics processes. The catalog has been elaborated during several workshops in the research project IMAGINE and results from a systematic process analysis using e.g. OMEGA and material flow methods. Furthermore, all identified AI use cases are assessed regarding their effort-benefit ratio based on a survey with domain experts and AI experts of three involved manufacturing companies and two research institutes. Both the use case catalog and the assessment show promising AI applications in intralogistics and thus support decision-makers in the strategic planning and implementation of AI.