Reis, LeaLeaReis0000-0002-6607-0517Maier, ChristianChristianMaier0000-0001-8328-24932023-01-242023-01-242023978-1-4503-9231-0https://fis.uni-bamberg.de/handle/uniba/57789Abstract: What can we do to address the rising numbers of people suffering from mental health problems facing the lack of mental health professionals? This study uses 15 qualitative expert interviews to identify six realistic application scenarios for artificial intelligence in mental health that reduce mental health professionals' workload and improve treatment. We classify the application scenarios concerning the type of intelligence they embed (mechanical, analytical, emotional) and the type of task they support (automation, decision support, engagement) to assess their implementation readiness and success. Based on this classification, we develop four application scenarios with the potential for immediate implementation and two possible future directions. Our results contribute to the research stream of artificial intelligence in general and in mental health.engconferenceobject10.1145/3510606.3550209